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DTSTART;TZID=America/Toronto:20260508T130000
DTEND;TZID=America/Toronto:20260508T140000
DTSTAMP:20260530T152956
CREATED:20260224T202745Z
LAST-MODIFIED:20260408T015009Z
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SUMMARY:NISS-CANSSI Collaborative Data Science: Bayesian Reconstruction of Ion Temperature and Amplitude Profiles in Inertial Confinement Fusion Diagnostics
DESCRIPTION:Date: Friday\, May 8\, 2026\nTime: 13:00–14:00 Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for “Bayesian Reconstruction of Ion Temperature and Amplitude Profiles in Inertial Confinement Fusion Diagnostics” at the May NISS-CANSSI Collaborative Data Science Webinar. \nREGISTER ON ZOOM \nPresentation Abstract\nInertial confinement fusion (ICF) experiments rely on accurate ion temperature and emission measurements to diagnose plasma conditions and improve performance. However\, due to technical challenges and limited signal\, existing ion temperature diagnostics lack spatial resolution\, integrating measurements over the neutron source. The speakers present a Bayesian framework that uses Gaussian processes to model spatially varying ion temperature and emission amplitude profiles from imaging data. The approach combines a forward physics model with Markov Chain Monte Carlo inference to reconstruct profiles from synthetic datasets generated under realistic conditions\, while providing uncertainty quantification through posterior credible intervals. Results show that the GP-based model can recover spatially resolved temperature and amplitude structure with quantified uncertainty\, enabling a new capability for ICF experiments. \nThe webinar will feature Ky D. Potter (Statistics PhD candidate at Simon Fraser University) and Chris Danly (Director’s Postdoctoral Fellow at Los Alamos National Laboratory (LANL)). It will be moderated by Emily Casleton (Los Alamos National Laboratory and Chair of the NISS-CANSSI Collaborative Data Science Webinar Planning Committee). \nAbout the Speakers\nKy D. Potter is a Statistics PhD candidate at Simon Fraser University and a Graduate Student Intern in the Statistical Sciences Group (CAI-4) at Los Alamos National Laboratory. Their work sits at the intersection of Bayesian statistics and physics\, with applications spanning inertial confinement fusion\, space and ionospheric physics\, and astrostatistics. Ky focuses on scalable Gaussian process models\, uncertainty quantification\, and statistical emulation for complex\, noisy data. Ky enjoys collaborative\, interdisciplinary research at the interface of statistics and the physical sciences.\nChris Danly is a Director’s Postdoctoral Fellow at Los Alamos National Laboratory. He received his PhD in plasma physics from the University of Rochester and holds master’s degrees in physics and nuclear engineering. Since 2010\, Chris has been a member of LANL’s nuclear imaging team\, leading development of new imaging techniques to diagnose inertial confinement fusion and high energy density physics experiments. He recently joined the lab’s Analysis division\, where his research focuses on applications of fusion ignition\, and global security implications of the private fusion R&D boom.\n\nAbout the Moderator\nEmily Casleton is Chair of the NISS-CANSSI Collaborative Data Science Webinar Planning Committee. She is a statistician in the statistical sciences group at Los Alamos National Laboratory (LANL)\, and was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015\, Emily has routinely collaborated with seismologists\, nuclear engineers\, physicists\, geologists\, chemists\, and computer scientists on a wide variety of cool data-driven projects. Most recently\, her research focus has been on testing and evaluating large AI models. She holds a BS in Mathematics\, Political Science from Washington & Jefferson College\, 2003; an MS in Statistics from West Virginia University\, 2006; and a PhD in Statistics from Iowa State University. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-may2026/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-May-8-EN.png
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BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20260506T120000
DTEND;TZID=America/Vancouver:20260506T133000
DTSTAMP:20260530T152956
CREATED:20260318T174349Z
LAST-MODIFIED:20260413T042231Z
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SUMMARY:EDI Workshop: The Myths vs. Realities of Faculty Leadership
DESCRIPTION:As part of its professional development initiatives\, CANSSI is pleased to offer a workshop designed for faculty considering or transitioning into leadership roles. For many faculty\, moving into a leadership position can conjure images of sacrifice or the “dark side\,” but it can also present meaningful opportunities to make a positive impact within your institution. \n\nWe invite you to join this 90-minute session\, where we’ll debunk some of the myths surrounding faculty leadership and explore practical ways that taking on a leadership role can yield impactful engagement. You will also reflect on your own beliefs about leadership and identify the pros and cons of stepping into such a role. \nRegistration\nREGISTER FOR THIS WORKSHOP \n  \n\nWorkshop Leader\n \nCorinne Nicolas\, PhD\, PCC\n\nCorinne is Academic Impressions’ Head of Practice for Faculty Success\, a member of the Coaching Team\, and an ICF-certified coach. As the Head of Practice\, she partners with institutions to design and facilitate trainings and programs that foster the development of the leadership skills and mindsets needed for faculty to thrive\, advance in their careers\, and engage in sustainable\, high-impact leadership within their institutions. \nCorinne is deeply committed to supporting the professional growth of faculty and aspiring leaders so they can expand their professional impact. Her passion for this work stems from a 25-year career in higher education\, as a faculty and mid-level faculty leader in both liberal arts college and research university settings\, where she learned alongside and led colleagues navigating diverse stages of academic life. That commitment inspired her “second act”: leaving academia to launch her own coaching practice dedicated to serving faculty and academic leaders\, and eventually joining Academic Impressions in 2023. \nBorn and raised in France\, Corinne earned a PhD in English Composition from Indiana University of Pennsylvania\, as well as Master’s degrees\, in Education and English respectively\, from Tusculum University and the University of Haute Bretagne\, France. She is an avid beach lover\, who likes to experience new places\, values time with her family and is on a quest to bake the perfect baguette.
URL:https://canssi.ca/events/edi-workshop-the-myths-vs-realities-of-faculty-leadership/
CATEGORIES:CANSSI National,EDI
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20260501T093000
DTEND;TZID=America/Vancouver:20260501T154500
DTSTAMP:20260530T152956
CREATED:20260109T051030Z
LAST-MODIFIED:20260427T162122Z
UID:28606-1777627800-1777650300@canssi.ca
SUMMARY:Florence Nightingale Day 2026 at Simon Fraser University
DESCRIPTION:On May 1\, CANSSI and the Department of Statistics and Actuarial Science will celebrate Florence Nightingale Day 2026 at Simon Fraser University! \nThis one-day event is part of an international celebration that gives high school students\, especially those from traditionally under-represented groups\, a chance to explore educational and career opportunities in statistics and data science. It is named after Florence Nightingale\, the widely known founder of modern nursing who was also a ground-breaking statistician credited with inventing the pie chart. \nSFU’s Florence Nightingale Day 2026 will take place at the university’s Burnaby campus and will include fun hands-on activities\, panel discussions featuring university students and professionals\, and opportunities for participants to ask questions about studying and working in statistics and data science. The day has three goals: \n\nTo give participants an understanding of the strong benefits of studying statistics and data science for their future career paths\nTo give participants a glimpse of what studying statistics and data science in university is like\nTo promote diversity in statistics and data science by encouraging and inspiring high school students from all communities to explore statistical sciences\n\nLunch is free for all participating students and teachers. \nWhat Happens at Florence Nightingale Day\nWhat does the day look like? Check out these stories and photos from past events: \n\nFlorence Nightingale Day 2024\nFlorence Nightingale Day 2023\n\n\nFlorence Nightingale Day gives high school students a chance to ask questions and explore activities related to statistics and data science.\n\nHow to Participate\nSpace is limited\, and we can’t guarantee that everyone who signs up will be able to participate. Please use the links below to express your interest\, and we will follow up to confirm your participation. \nHigh School Teachers\nIf you would like to bring your class or a group of students to Florence Nightingale Day 2026\, we can make it easy by providing transportation and a free lunch for you and your students. \nNOTE: We have reached our capacity and are no longer accepting group applications for this year. If you would like to be put on a list for next year\, please contact us at info@canssi.ca to express your interest. \n\n\nStudents\nIf you would like to attend on your own\, please sign up here and we’ll contact you as soon as possible. \n\nNote that we can reimburse you for your travel costs to and from the event. \n\nVolunteers\nWe are looking for individuals to help us plan and organize the activities for this event. \nIf you are interested in helping out either before the event or on the day\, please sign up here to get more information. \nSchedule of Activities\n(Tentative schedule; all times are Pacific Time) \n\n\n\n\nTime\nActivity\n\n\n9.30–9:45\nRegistration\n\n\n9:45–10:15\nWelcome and Icebreaker Game\n\n\n10:15–11:00\nUndergraduate and Graduate Student Panel \n\n\nDaniel Smith (Undergraduate\, Data Science)\n\n\nFergus Dalton (Master’s Student\, History\, Quantitative\, and Theoretical (HQT) Psychology)\n\n\nDeclan O’Sullivan (Undergraduate\,  Molecular Biology and Biochemistry Major)\n\n\nSarah Jassim (Undergraduate\, Health Science)\n\n\nNancy Nanqian Tang (Undergraduate\, Actuarial Science)\n\n\n\n\n\n11:00–11:15\nBreak\n\n\n11:15–12:30\nInteractive Activities\n\n\n12:30–1:15\nLunch\n\n\n 1:15–2:00\nCareer Panel \n\nKristen Basaraba (Staff Data Scientist\, Workstream)\nZhi Yuh Ou Yang (Data Analyst\, BC Centre for Disease Control)\nZubia Mansoor (Manager\, AI at Lululemon)\nDuong Vu (Senior Data Scientist\, MasterCard)\nJacob Sande (Actuarial Analyst\, Milliman)\n\n\n\n\n2:00–2:15\nWrap-up\n\n\n\n\nAbout Florence Nightingale Day\nFlorence Nightingale Day was launched in the U.S. in 2018. Since then\, it has become an international initiative with in-person activities for local high school students organized at colleges and universities and virtual activities for students from all over the world. In the U.S.\, it has been celebrated at a number of institutions\, including Ohio State University\, Harvard University\, and the University of Texas at Dallas. In Canada\, it has been celebrated at many post-secondary institutions\, including Simon Fraser University\, the University of Alberta\, the University of Toronto (co-sponsored by CANSSI Ontario)\, York University\, the Université de Montréal\, and the University of New Brunswick. \nCANSSI is a major co-sponsor and co-organizer of Florence Nightingale Day together with the Caucus for Women in Statistics and the American Statistical Association. It’s part of our effort to attract high school students from traditionally under-represented and disadvantaged groups to study statistics and data science. Our vision is to expand Florence Nightingale Day to become a national event involving high school students across Canada. \nIn 2026\, CANSSI will support events at multiple locations. Our goal is to expand the number of sites each year. Check out these photos from the Florence Nightingale Day 2024 celebrations organized by CANSSI and the hosting universities. \nFor an international list of upcoming Florence Nightingale Day celebrations\, visit this page.
URL:https://canssi.ca/events/fnday-2026-at-sfu/
LOCATION:Simon Fraser University (Halpern Centre)\, Burnaby\, British Columbia\, V5A 1S6\, Canada
CATEGORIES:CANSSI National,EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/FN-Day-2026-at-SFU-Alt1-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20260212T130000
DTEND;TZID=America/Toronto:20260212T140000
DTSTAMP:20260530T152956
CREATED:20260203T034446Z
LAST-MODIFIED:20260211T192027Z
UID:28822-1770901200-1770904800@canssi.ca
SUMMARY:Cancelled: NISS-CANSSI Collaborative Data Science: Exploring Future Directions for the NISS-CANSSI Collaborative Data Science Series
DESCRIPTION:Date: Thursday\, February 12\, 2026\nTime: 13:00–14:00 Eastern time\nLocation: CANCELLED \nJoin Us\nThis event has been cancelled. \nJoin us for this special community roundtable on “Exploring Future Directions for the NISS/CANSSI Collaborative Data Science Series.” We would love to have your input. \nPresentation Abstract\nThe NISS-CANSSI Collaborative Data Science webinar series is dedicated to showcasing the power of interdisciplinary collaboration between data scientists and domain experts. This initiative celebrates how the fusion of data science with diverse scientific fields can drive innovation\, solve complex problems\, and push the boundaries of knowledge. In this webinar\, the members of the organizing committee will introduce themselves and provide an overview of the web series. The goal is to engage the community and gather feedback on the types of collaborations and topics community members would like to see featured in future sessions. \nAttendees will have the opportunity to: \n\nMeet the members of the organizing committee and learn about their backgrounds and expertise\nUnderstand the vision and goals of the NISS-CANSSI Collaborative Data Science webinar series\nProvide input and suggestions on the types of collaborations\, scientific domains\, and emerging topics they would like to see highlighted\n\nThis interactive session will help shape the direction of the webinar series\, ensuring that it continues to be a valuable resource for showcasing the transformative impact of collaborative data science. Join us to be a part of this exciting initiative and help shape the future of cross-disciplinary research and discovery. \nPlanning Committee Members\nQingzhao Yu\, Associate Dean for Research at the School of Public Health\, Louisiana State University Health Sciences Center\, New Orleans \nDon Estep\, Director\, Canadian Statistical Sciences Institute (CANSSI)\, Canada Research Chair (Tier 1)\, Department of Statistics and Actuarial Science\, Simon Fraser University \nXiao-Li Meng\, Whipple V.N. Jones Professor of Statistics\, Harvard University \nSaman Muthukumarana\, Director\, Data Science Nexus and Professor and Head\, Department of Statistics\, University of Manitoba \nSahar Zengeneh\, Cascade Insights LLC \nElizabeth Eisenhauer\, Senior Statistical Associate\, Westat \nJiguo Cao\, Canada Research Chair in Data Science\, Professor\, Department of Statistics and Actuarial Science\, Simon Fraser University \nJoel Dubin\, Professor\, Statistics and Actuarial Science\, ​Health Data Science Lab (HDSL) Lead\, University of Waterloo \nDavid S. Matteson\, Director\, NISS\, and Professor\, Department of Statistics\, Cornell University \n\nAbout the Moderator\n \nEmily Casleton is Chair of the NISS-CANSSI Collaborative Data Science Webinar Planning Committee. She is a statistician in the statistical sciences group at Los Alamos National Laboratory (LANL)\, and was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015\, Emily has routinely collaborated with seismologists\, nuclear engineers\, physicists\, geologists\, chemists\, and computer scientists on a wide variety of cool data-driven projects. Most recently\, her research focus has been on testing and evaluating large AI models. She holds a BS in Mathematics\, Political Science from Washington & Jefferson College\, 2003; an MS in Statistics from West Virginia University\, 2006; and a PhD in Statistics from Iowa State University. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-feb2026/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Feb-12-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20260115T120000
DTEND;TZID=America/Toronto:20260115T130000
DTSTAMP:20260530T152956
CREATED:20260114T050953Z
LAST-MODIFIED:20260114T175501Z
UID:28647-1768478400-1768482000@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science: Advancing Neonatal and Perinatal Research Through Collaborative Biostatistical Innovation
DESCRIPTION:Date: Thursday\, January 15\, 2026\nTime: 12:00–13:00 Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for “Advancing Neonatal and Perinatal Research Through Collaborative Biostatistical Innovation” at the next NISS-CANSSI Collaborative Data Science Webinar. \nREGISTER ON ZOOM \nPresentation Abstract\nThis session will focus on the role of modern data science and statistical methodology in advancing neonatal and perinatal research. The session will explore how rigorous study design\, innovative analytic approaches\, and careful treatment of uncertainty support high-impact clinical trials and observational studies in maternal and child health. Emphasis will be placed on the challenges of working with complex\, multicentre clinical data\, the integration of clinical expertise with statistical reasoning\, and the translation of data-driven evidence into practice. The webinar will be of interest to researchers and practitioners engaged in biostatistics\, data science\, and interdisciplinary health research who seek to strengthen the methodological foundations of clinical and population-based studies. \nThis webinar will feature Anup Katheria (Associate Professor of Pediatrics at Drexel University College of Medicine and Director of the Neonatal Research institute at Sharp Mary Birch Hospital for Women & Newborns) and Abhik Das (Distinguished Fellow\, Biostatistics\, at RTI International). It will be moderated by Sahar Zangeneh (Cascade Insights LLP). \nAbout the Speakers\n \nAnup Katheria is an Associate Professor of Pediatrics at Drexel University College of Medicine\, and the Director of the Neonatal Research institute at Sharp Mary Birch Hospital for Women & Newborns. Interests are in functional echocardiography\, point of care ultrasound\, and conducting clinical trials. I am currently conducting several large multi-centre trials: 1. comparing cord milking to early cord clamping in term non-vigorous infants; 2. comparing delayed cord clamping to umbilical cord milking in preterm infants; 3. comparing empiric antibiotic therapy to placebo in extremely low birthweight infants; 4. comparing early continuous positive airway pressure (CPAP) to early caffeine plus less invasive surfactant administration (LISA); 5. evaluating the use of cromolyn sodium therapy to reduce bronchopulmonary dysplasia (BPD); 6. comparing the effectiveness of nasal high-flow cannula to CPAP. Dr. Katheria earned his BS in Biology from the University of California\, Los Angeles\, his MD from Drexel University College of Medicine\, completed his pediatric residency at Children’s Hospital of Orange County\, and his Neonatal-Perinatal Fellowship at the University of California\, San Diego. See profile. \n\nAbhik Das is a Distinguished Fellow in Biostatistics. Having led the Data Coordination Center for the NICHD Neonatal Research Network (NRN) for 16 years\, Dr. Das is an expert in modelling\, analyzing\, and interpreting public health data. He has a wealth of experience in the design of intervention studies\, including randomized clinical trials\, and he also provides statistical expertise in neonatology\, substance abuse\, health insurance coverage\, diabetes\, and maternal and child health. Since 1999\, Dr. Das has been providing biostatistical leadership for multicentre clinical studies in neonates. As the Principal Investigator for the Data Coordinating Center for the NRN\, he helped design\, implement\, monitor\, analyze and publish 30-plus multicentre randomized controlled trials\, 20-plus observational studies\, and 200-plus publications in perinatology that have informed clinical practice. Dr. Das has designed and analyzed studies in perinatal settings spanning a variety of designs\, including Bayesian\, pragmatic comparative effectiveness\, comprehensive cohort\, factorial\, cluster randomized\, phase II and pharmacokinetic studies. He has a wide range of experience in a variety of areas\, including studying near-term and neurodevelopmental morbidities\, fetal alcohol effects\, effects of prenatal substance use on development\, pharmacologic interventions under investigational new drug application\, and international trials in maternal-infant nutrition. Dr. Das is a member of the Society for Pediatric Research. He serves as the Associate Editor for the American Journal of Perinatology. Additionally\, he is a reviewer on several journals\, including JAMA Pediatrics and the Journal of Pediatrics. Dr. Das is also a reviewer on several study sections and data and safety monitoring committees associated with the National Institutes of Health (NIH)\, the National Science Foundation\, and more. See profile. \n\n\nAbout the Moderator\n\nSahar Zangeneh is a statistician at Cascade Insights LLP with broad expertise in the design and analysis of clinical and epidemiological studies. Her work draws on extensive experience with secondary data sources\, including electronic health records\, claims data\, and disease registries\, and she has strong methodological expertise in missing data\, causal inference\, and multilevel modelling. Sahar is deeply committed to interdisciplinary research and values team building and collaboration to address complex scientific questions. Previously\, Dr. Zangeneh served as a Senior Research Statistician at RTI\, where she specialized in the design and analysis of complex sample surveys and developed novel statistical methods for non-ignorable missing data. Her methodological research integrates classical and modern approaches\, including parametric and nonparametric likelihood-based methods\, Bayesian modelling\, and machine learning tools. Her contributions have been recognized with multiple awards from professional societies\, including the American Statistical Association\, the International Society for Bayesian Analysis\, and the Institute of Mathematical Statistics. Before joining RTI in 2021\, Dr. Zangeneh was a faculty biostatistician in the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center\, where she also completed her postdoctoral training. There\, she conducted research focused on HIV and COVID-19 prevention and led the analysis of both observational and interventional studies\, developing and implementing research protocols for diverse domestic and international health projects. She is also a Clinical Instructor at the University of Washington in Seattle\, where she teaches and contributes to graduate-level curriculum development. Dr. Zangeneh is a member of several professional organizations\, including the American Statistical Association\, Institute for Mathematical Statistics\, International Statistical Institute\, International Society for Bayesian Analysis\, and the Iranian Statistical Society\, and she is deeply committed to advancing inclusion\, diversity\, and STEM engagement for underrepresented and underserved students. See profile. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-jan2026/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Jan-15-EN-R1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20251120T130000
DTEND;TZID=America/Toronto:20251120T140000
DTSTAMP:20260530T152956
CREATED:20251114T001157Z
LAST-MODIFIED:20251114T005126Z
UID:28454-1763643600-1763647200@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science: Deep Learning with ECG Data in the ICU: From Modelling to Actionable AI
DESCRIPTION:Date: Thursday\, November 20\, 2025\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for “Deep Learning with ECG Data in the ICU: From Modelling to Actionable AI” at the next NISS-CANSSI Collaborative Data Science Webinar. \nPresentation Abstract\nThis session will examine how deep learning methods can be leveraged to analyze electrocardiogram (ECG) data collected in intensive care units (ICUs)\, where rapid\, reliable interpretation of patient information is crucial. The discussion will span the full pipeline—from methodological advances in modelling ECG signals to the translation of AI-driven insights into tools that can support real-time decision-making at the bedside. Together\, the speakers will bridge perspectives from computer science and clinical practice\, offering insights into both the technical challenges of modelling high-dimensional physiological time-series data and the practical considerations required to make AI trustworthy\, interpretable\, and actionable in critical care environments. \nThis webinar will feature David Maslove (Queen’s University and Kingston Health Sciences Centre) and Parvin Mousavi (Queen’s University). It will be moderated by Joel Dubin (University of Waterloo). \nREGISTER ON ZOOM \nAbout the Speakers\n \nDavid Maslove is a Clinician Scientist in the Departments of Medicine and Critical Care Medicine at Queen’s University\, and an Internist and Intensivist at Kingston Health Sciences Centre. His research focuses on the use of physiologic and genomic data to advance precision medicine in the ICU. Dr. Maslove completed medical school and residency in Internal Medicine at the University of Toronto. He trained in Critical Care Medicine at Stanford University where he also completed graduate studies in Biomedical Informatics. He is a member of the Canadian Critical Care Trials Group\, and the Society of Critical Care Medicine\, and since 2018 has been the Associate Editor for Data Science for Critical Care Medicine. See profile \n\nParvin Mousavi is the Director of the School of Computing at Queen’s University. Her research interests are in computer-aided diagnosis and interventions. These include: \n\nMachine learning techniques for in silico inference and prediction\nAnalysis of ultrasound images and signals for enhancement of cancer detection\nImage-aided\, computer-assisted diagnosis of disease\nUltrasound-guided interventions\nKnowledge discovery from high-throughput biological data\nQuantitative modelling and reverse engineering of gene regulatory networks\nAnalysis\, segmentation and classification of fluorescence microscopy images\nChromosome and cell imaging. See profile.\n\n\n\nAbout the Moderator\n\nJoel Dubin is a leading methodological statistician whose work focuses on longitudinal data analysis\, especially multivariate and time-varying outcomes. He develops tools for modelling multiple physiological measurements over time—such as heart rate\, respiratory rate\, or blood pressure—using advanced techniques like curve-based methods\, derivatives\, and lagged effects. He also works on change-point and latent response models\, prediction models that leverage subject similarity\, and methods to handle missingness and complexity in real-world health data. His research spans a range of applications including intensive care\, electronic health records\, mobile health\, child and aging populations\, nephrology\, cancer\, nutrition\, smoking cessation\, and environmental health. Dr. Dubin received his MS in Applied Statistics from Villanova University\, then worked in health services research at the U.S. Veterans Affairs and the MD Anderson Cancer Center. He earned his PhD in Statistics from the University of California-Davis\, followed by a faculty appointment at Yale University. In 2005 he joined the University of Waterloo with a joint appointment in Statistics & Actuarial Science and Health Studies & Gerontology (now the School of Public Health Sciences). See profile. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-nov2025/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Nov-20-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20251009T130000
DTEND;TZID=America/Toronto:20251009T140000
DTSTAMP:20260530T152956
CREATED:20250924T000627Z
LAST-MODIFIED:20251008T041857Z
UID:28307-1760014800-1760018400@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science: Working with Physicists on Quantum ML
DESCRIPTION:Date: Thursday\, October 9\, 2025\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for “Working with Physicists on Quantum ML” at the next NISS-CANSSI Collaborative Data Science Webinar. \nPresentation Abstract\nThe National Institute of Statistical Sciences (NISS) and the Canadian Statistical Sciences Institute (CANSSI) are pleased to present a collaborative webinar exploring the emerging field of Quantum Machine Learning (QML). This session will bring together physicists at the forefront of quantum research to share how quantum principles are reshaping machine learning and data science. \nParticipants will gain insight into the foundations of QML\, its potential to revolutionize data-driven discovery\, and the unique challenges of bridging physics\, computation\, and statistics. Designed for a broad audience of statisticians\, data scientists\, and researchers\, this event will highlight both theoretical perspectives and practical applications\, offering a unique opportunity to learn directly from experts working at the intersection of quantum science and machine learning. \nREGISTER ON ZOOM \nAbout the Speakers\nDr. Martin T. Wells is a prominent figure at Cornell University\, specializing in statistical sciences. He has been with the Cornell faculty since 1987 and holds the title of Charles A. Alexander Professor of Statistical Sciences. Dr. Wells is also a professor of social statistics\, biostatistics\, and epidemiology at Weill Medical School\, and an elected member of the Cornell Law School faculty. His research interests span applied and theoretical statistics\, with a focus on inference questions in various fields such as credit risk\, economic damages\, and legal studies. Dr. Wells has published numerous articles in leading statistical journals and has served on high-level national statistical committees. He is also the Editor in Chief of ASA-SIAM Series on Statistics and Applied Probability and has contributed to the development of statistical methodologies for various scientific disciplines. See profile. \nDr. Luca Candelori is a mathematician and currently Director of Research at Qognitive\, Inc. He received a BA in mathematics from Harvard University in 2008 and a PhD in mathematics from McGill University in 2014\, specializing in number theory and algebraic geometry. In 2018 he joined the Department of Mathematics at Wayne State University (WSU)\, where he is now an Associate Professor (currently on leave). While at WSU\, he developed new ways of measuring quantum entanglement using geometric invariant theory\, as co-PI of a U.S. Department of Energy grant. Since 2023 he has been working with Qognitive\, Inc.\, first as a consultant and then full-time as Director of Research\, developing new machine learning models based on the mathematical formalism of quantum mechanics. Qognitive\, Inc.\, is a startup founded in 2023 by Dario Villani and Kharen Musaelian\, with the goal of developing and deploying models based on Quantum Cognition Machine Learning (QCML). QCML is a new form of machine learning that is inspired by quantum cognition. QCML models learn a representation of the input data into quantum states\, and the outputs of the models reflect the outcomes of quantum measurements. QCML is highly effective on datasets with a large number of input features and a large number of classes (for classification) or targets (for regression). Qognitive has developed products for analyzing similarity of complex financial instruments\, as well as analyzing similarity between patients using medical insurance claims data. See profile.\n\nAbout the Moderator\nEmily Casleton is a statistician in the statistical sciences group at Los Alamos National Laboratory (LANL)\, and was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015\, Emily has routinely collaborated with seismologists\, nuclear engineers\, physicists\, geologists\, chemists\, and computer scientists on a wide variety of cool data-driven projects. Most recently\, her research focus has been on testing and evaluating large AI models. She holds a BS in Mathematics\, Political Science from Washington & Jefferson College\, 2003; an MS in Statistics from West Virginia University\, 2006; and a PhD in Statistics from Iowa State University. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session features two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-oct2025/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Oct-9-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250924T120000
DTEND;TZID=America/Toronto:20250924T143000
DTSTAMP:20260530T152956
CREATED:20250520T231441Z
LAST-MODIFIED:20250612T164419Z
UID:27820-1758715200-1758724200@canssi.ca
SUMMARY:EDI Workshop: Prévention et gestion des conflits en contexte de diversité
DESCRIPTION:As part of its Equity\, Diversity\, and Inclusion (EDI) program\, CANSSI regularly organizes EDI workshops and training sessions for the statistical sciences community. Our next session is a French-language webinar presented by URelles\, a Montreal-based EDI training provider whose mission is “to help Quebec organizations create inclusive and equitable cultures in order to position themselves as employers of choice.” URelles was established in 2019 and has worked with major Quebec-based companies and organizations\, including STM\, L’Oreal\, BAnQ\, Sobeys\, and Ordre des CPA du Québec. It is built upon the belief that “diversity of experience\, viewpoint and background is an invaluable source of wealth and innovation.” \nWe invite you to join us for “Prévention et gestion des conflits en contexte de diversité” (Conflict Prevention and Management in a Diversity Context)\, a 2.5-hour online workshop led by Chloé Freslon\, Founder of URelles. \nThis session can be used to fulfill the CANSSI EDI requirement for CANSSI-supported researchers. \nRegistration\nREGISTER FOR THIS WORKSHOP \nWorkshop Description\nTeams composed of people with diverse backgrounds\, perspectives\, and experiences are an invaluable asset for any organization. However\, these differences can sometimes give rise to misunderstandings or tensions. This training provides you with the tools to prevent conflicts\, manage disagreements constructively\, and turn differences into levers for collaboration and innovation. Because at the end of the day\, we’re still colleagues who must collaborate! \n\nWorkshop Leader\nChloé Freslon\nFounder of URelles\n \nAfter working for nearly 15 years in the technology industry\, with both large corporations and SMEs (small and medium-sized enterprises)\, Chloé became aware of the consequences of a homogeneous workforce. At the time\, she was working for the media outlet Journal Métro and decided to seize this opportunity to talk about the lack of representation in organizations. URelles was born! Chloé is an accredited trainer with the Commission des partenaires du marché du travail (CPMT).  She was one of the six experts who participated in the very first report on psychological and sexual harassment in IT in Quebec\, produced by TECHNOcompétences. She won the “Champion of Diversity” award at the Startup Community Awards. She writes monthly columns on diversity and inclusion for the HEC magazine\, Revue Gestion.
URL:https://canssi.ca/events/prevention-et-gestion-des-conflits/
CATEGORIES:CANSSI National,EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/EDI-French-2025-Sep-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250613T100000
DTEND;TZID=America/Vancouver:20250613T110000
DTSTAMP:20260530T152956
CREATED:20250507T182403Z
LAST-MODIFIED:20250521T155838Z
UID:27767-1749808800-1749812400@canssi.ca
SUMMARY:2025 CANSSI Town Hall
DESCRIPTION:Get the big picture on what CANSSI has been—and will be—doing by attending the 2025 CANSSI Town Hall. \nThis year’s Town Hall will take place on Friday\, June 13\, from 10:00 to 11:00 a.m. PT\, on Zoom. \nIt is open to all members of the statistical sciences community and will feature a fast-paced overview of CANSSI’s recent activities and plans for the next two years from Director Don Estep. \nWe invite you to join your colleagues from across Canada for this session. \nREGISTER ON EVENTBRITE \nOnce you have registered\, you will receive a Zoom link for the session via email. \nAgenda\n\nReport on the CANSSI National Retreat\nUpdate on plans for a National Report on Canadian Statistics\nSchedule of activities for the next 2 years\n\nNOTE: If you are a CANSSI representative for your university\, note that the Town Hall will occur immediately after the 2025 CANSSI Annual General Meeting (AGM)\, which will take place from 9:30 to 10:00 a.m. PT\, also on Zoom. CANSSI representatives will receive materials and a Zoom link for the AGM via email.
URL:https://canssi.ca/events/2025-canssi-town-hall/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Town-Hall-2025-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250610T130000
DTEND;TZID=America/Toronto:20250610T140000
DTSTAMP:20260530T152956
CREATED:20250427T191101Z
LAST-MODIFIED:20250606T003754Z
UID:27712-1749560400-1749564000@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science Webinar: Data Science Techniques for Control of Assistive Devices after Neurological Injury
DESCRIPTION:Date: Tuesday\, June 10\, 2025 – NEW DATE!\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for the next NISS-CANSSI Collaborative Data Science Webinar\, titled “Data Science Techniques for Control of Assistive Devices after Neurological Injury.” \nPresentation Abstract\nJoin us for an enlightening session that promises to showcase the transformative power of data science in improving the lives of those affected by neurological injuries! CANSSI and the National Institute of Statistical Sciences (NISS) are excited to announce a collaborative webinar focusing on innovative data science techniques for controlling assistive devices after neurological injury. This event aims to bring together experts in data science\, neurology\, and assistive technology to discuss cutting-edge research and practical applications that can significantly improve the quality of life for individuals with neurological impairments. This webinar is ideal for researchers\, clinicians\, data scientists\, engineers\, and anyone interested in the intersection of data science and assistive technology. Whether you are directly involved in the development of assistive devices or simply curious about the advancements in this field\, this event will provide valuable insights and networking opportunities. \nKey topics: \n\nAdvanced data science methods: Explore the latest techniques in data analysis and machine learning that are being used to enhance the functionality and responsiveness of assistive devices.\nNeurological injury and rehabilitation: Understand the challenges faced by individuals with neurological injuries and how data-driven solutions can aid in their rehabilitation.\nCase studies and applications: Learn from real-world examples where data science has been successfully implemented to control assistive devices\, improving patient outcomes.\nFuture directions: Discuss the future of assistive technology and the role of data science in developing more sophisticated and personalized solutions.\n\nREGISTER ON ZOOM \nAbout the Speakers\n Dr. Lauren Wengerd’s educational and career experiences have led her to the intersection of healthcare\, research\, and business. She recently completed a PhD in Health and Rehabilitation Sciences with a graduate minor in neuroscience at The Ohio State University. Her research primarily focuses on identifying new and effective interventions to maximize function and independence for adults with neurological conditions. She is passionate about identifying not only effective but also cost-effective approaches to healthcare. She regularly incorporates cost-effectiveness analyses into clinical study design to bridge the gap between research and clinical care. Dr. Wengerd holds a master’s degree in occupational therapy and a bachelor’s degree in business administration/marketing\, both of which continue to serve her well in research and clinical consulting roles. She is actively pursuing a career that will cultivate her knowledge and passion for healthcare\, research\, and business to ultimately enhance the quality of life and functional independence of individuals with neurological injuries. \nDr. David Friedenberg is a Principal – Data Science and Neurotechnology and the Team Lead for Machine Learning/AI in the Advanced Analytics group at Battelle. He is the PI on several neurotechnology efforts developing new AI-powered technologies to help improve the lives of people living with motor impairments due to neurological injuries like spinal cord injuries and stroke. An experienced data scientist with consulting experience across several disciplines\, he is passionate about developing AI/ML-driven solutions to challenging problems for the betterment of humanity.\n\nAbout the Moderator\nNancy McMillan currently serves as Data Science Research Leader within Battelle’s Health Research & Analytics Business Line. For a diverse set of federal government clients\, she leads development of a large language model (LLM)–based biocuration acceleration pipeline and user tool\, development of pipelines\, analytics\, and visualizations of electronic initial case reporting data\, and development of analytical methods for achieving abbreviated new drug application (ANDA) approval for an agile drug manufacturing technology. Nancy has a long history of collaborative work across Battelle bringing statistics and machine learning to Battelle’s deep capability in biology\, chemistry\, and material science. As a Researcher and Project Management Professional\, Nancy has worked and published on environmental exposure and risk assessment; transportation safety benefits; quantitative risk assessment related to chemical\, biological\, radiological\, and nuclear (CBRN) terrorism; bio surveillance; and bioinformatics. She managed the Health Analytics Division from 2017 to 2023\, a team of approximately 100 data scientists that supports Battelle’s contract research business. Nancy is a member of the Board of Trustees for the National Institute of Statistical Sciences (NISS)\, the Chair of NISS’s Affiliates Committee\, and a member of the Organ Procurement and Transplantation Network’s Data Advisory Committee. \n\n\nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session will feature two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees will gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars will not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-jun2025/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Jun-10-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Regina:20250524T080000
DTEND;TZID=America/Regina:20250524T180000
DTSTAMP:20260530T152956
CREATED:20250219T182550Z
LAST-MODIFIED:20250515T002215Z
UID:27341-1748073600-1748109600@canssi.ca
SUMMARY:Canadian Statistics Student Conference 2025
DESCRIPTION:Date: Saturday\, May 24\, 2025\nTime: All day\nLocation: University of Saskatchewan\, 105 Administration Place\, Saskatoon\, Sask. S7N 5A2 \nCANSSI is proud to be a co-sponsor of the Thirteenth Annual Canadian Statistics Student Conference (CSSC 2025). \nCSSC 2025 will take place at the University of Saskatchewan in Saskatoon\, Saskatchewan\, on Saturday\, May 24\, 2025\, the day before the 2025 Statistical Society of Canada Annual Meeting opens in the same location. \nThis conference is all about engaging students through research presentations\, statistical skills development workshops and talks\, and an interactive career session with invited statisticians from different professional areas. \nIt’s a wonderful opportunity for students to hear about and present their statistics-related research through oral presentations and posters. \nRegistration\nRegistration is now closed. \nVISIT THE CSSC 2025 WEBSITE FOR FULL DETAILS.
URL:https://canssi.ca/events/canadian-statistics-student-conference-2025/
LOCATION:University of Saskatchewan\, 105 Administration Place\, Saskatoon\, Saskatchewan\, S7N 5A2\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/jpeg:https://canssi.ca/wp-content/uploads/CSSC2025_en.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250508T130000
DTEND;TZID=America/Toronto:20250508T140000
DTSTAMP:20260530T152956
CREATED:20250416T011537Z
LAST-MODIFIED:20250423T015827Z
UID:27670-1746709200-1746712800@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science Webinar: From MPEG-4 to Deep Learning: Transforming Audio-Visual Analytics for Healthcare and Beyond
DESCRIPTION:Date: Thursday\, May 8\, 2025\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for the next NISS-CANSSI Collaborative Data Science Webinar\, titled “From MPEG-4 to Deep Learning: Transforming Audio-Visual Analytics for Healthcare and Beyond.” This webinar will explore the evolution of audio-visual analytics from traditional compression standards like MPEG-4 and H.264 to modern deep learning approaches that enable real-time object detection\, action recognition\, and intelligent healthcare applications. Advancements in deep learning have significantly redefined how we process image\, video\, and audio data\, making possible innovations such as robotic patient monitoring and voice-activated medical assistants. Often referred to as “orange technology\,” these integrated techniques are enhancing the quality of life in medical settings and transforming the landscape of healthcare and beyond. Don’t miss this opportunity to gain insights into how classical and modern methods converge to shape the future of audio-visual data science. \nPresentation Abstract\nOver the past two decades\, image and video processing has undergone a revolutionary transformation. Traditional standards such as MPEG-4 and H.264 laid the groundwork for efficient storage and transmission by exploiting motion estimation\, block-based transforms\, and predictive coding. More recently\, advanced deep learning models have significantly redefined the field\, offering higher accuracy and deeper insights into visual data. For example\, architectures like YOLO enable real-time object detection and facilitate tasks like region-of-interest tracking\, action recognition\, and video summarization. Simultaneously\, multi-view coding techniques—once reliant on handcrafted features—now benefit from data-driven optimization that leverages spatiotemporal coherence. This has led to robust motion estimation\, improved inter/intra-frame predictions\, and an expanded range of applications well beyond compression. Additionally\, integrating deep learning–based image and video processing with sound signal analysis paves the way for robotic agents in healthcare\, using camera feeds for patient monitoring and acoustic signals for voice-activated commands. Often termed “orange technology\,” these synergistic approaches enrich quality of life in medical settings. This webinar explores the shift from classical compression to advanced deep learning and highlights how these paradigms converge to drive innovations in healthcare\, robotics\, and beyond. \nREGISTER ON ZOOM \n\nAbout the Speakers\n Dr. An-Chao Tsai received his PhD in Electrical Engineering from National Cheng Kung University\, Taiwan\, in 2010. He is currently an Associate Professor in the International Master Program of Information Technology and Application at National Pingtung University\, Taiwan. His research focuses on artificial intelligence\, virtual reality\, and AIoT. Dr. Tsai has contributed extensively to AI-driven medical applications\, agricultural precision analysis\, and computer vision. His recent work includes AI-based skin analysis using conditional generative adversarial networks for melasma diagnosis\, real-time classification of black soldier fly larvae for sustainable food waste management\, and intelligent IoT-based farming systems for optimizing agricultural productivity. As a Senior Member of IEEE\, Dr. Tsai has served as the Track Chair and Program Chair for the IEEE International Conference on Orange Technologies since 2015. His interdisciplinary research integrates AI\, IoT\, and deep learning for practical\, real-world applications in healthcare\, smart agriculture\, and education. \nDr. Anand Paul is an Associate Professor in the Department of Biostatistics and Data Science at the School of Public Health\, Louisiana State University Health Sciences Center. He earned his PhD in Electrical and Computer Engineering from National Cheng Kung University\, Taiwan\, R.O.C.\, in 2010. His research interests encompass Big Data Analytics\, Artificial Intelligence (AI)\, and Machine Learning\, with a particular focus on Resilient and Robust Intelligence\, including Generative AI and Artificial General Intelligence. Dr. Paul was recognized among the top 2% of scientists worldwide by Stanford University and Elsevier Publisher for the years 2022 and 2024. He has been an IEEE Senior Member since 2015. In addition to his research\, Dr. Paul has served as an editor for several prestigious SCIE journals\, including IEEE Access\, Computer Animation and Virtual Worlds\, ICT Express\, PeerJ Computer Science\, Cyber-Physical Systems (Taylor & Francis)\, International Journal of Interactive Multimedia and Artificial Intelligence\, and ACM Applied Computing Review. He has also held the role of Track Chair for Smart Human-Computer Interaction at ACM SAC from 2014 to 2019. \nAbout the Moderator\nDr. Qingzhao Yu is a Biostatistics and Data Science Professor and the Associate Dean of Research at the School of Public Health\, Louisiana State University (LSU) Health-New Orleans. As a researcher\, Dr. Yu has developed statistical methods in causal inference\, clinical trials\, Bayesian methods\, spatial analysis\, data mining\, and machine learning methods. Her research areas of interest include health disparities\, cancer\, and chronic diseases. Dr. Yu has published over 140 methodology and collaboration papers and five software packages. She is a Co-Editor for the journal Data Science in Science. Dr. Yu is a PI and Co-Investigator for multiple grants supported by NIH\, CDC\, and other national and state funding agencies. \nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session will feature two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees will gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars will not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-may2025/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSS-CoLab-May-8-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250502T093000
DTEND;TZID=America/Vancouver:20250502T154500
DTSTAMP:20260530T152956
CREATED:20250121T193437Z
LAST-MODIFIED:20250331T234958Z
UID:27232-1746178200-1746200700@canssi.ca
SUMMARY:Florence Nightingale Day 2025 at Simon Fraser University
DESCRIPTION:Florence Nightingale Day 2025 at Simon Fraser University is coming up! This one-day event is part of an international celebration that gives high school students\, especially those from traditionally under-represented groups\, a chance to explore educational and career opportunities in statistical sciences. It is named after Florence Nightingale\, the widely known founder of modern nursing who was also a ground-breaking statistician credited with inventing the pie chart. \nIn British Columbia\, Florence Nightingale Day 2025 will be co-hosted on Friday\, May 2\, by the Canadian Statistical Sciences Institute (CANSSI) and Simon Fraser University (SFU)’s Department of Statistics and Actuarial Science. The event will take place at SFU’s Burnaby campus and will include fun hands-on activities\, panel discussions featuring university students and professionals\, and opportunities for participants to ask questions about studying and working in statistics. The day has three goals: \n\nTo give participants an understanding of the strong benefits of studying statistics for their future career paths\nTo give participants a glimpse of what studying statistics in university is like\nTo promote diversity in statistics and data science by encouraging and inspiring high school students from all communities to explore statistics\n\nLunch is free for all participating students and teachers! \nWhat Happens at Florence Nightingale Day\nWhat does the day look like? Check out these stories and photos from past events: \n\nFlorence Nightingale Day 2024\nFlorence Nightingale Day 2023\n\n\nFlorence Nightingale Day gives high school students a chance to ask questions and explore activities related to statistical sciences.\n\nHow to Participate\nSpace is limited for this event\, and we can’t guarantee that everyone who signs up will be able to participate. Please use the links below to express your interest\, and we will follow up to confirm your participation. \nHigh School Teachers\nIf you would like to bring your class or a group of students to Florence Nightingale Day 2025\, we can make it easy by providing transportation and a free lunch for you and your students. \nTo express your interest\, please fill out this form and we’ll contact you.* \n*We’ve reached our maximum capacity and can’t accept more classes for this year’s celebration. However\, we invite you to use the form to express your interest in bringing your class or group to next year’s celebration\, expected to take place in early May 2026. \nStudents\nIf you would like to attend on your own\, please sign up here and we’ll contact you. \nVolunteers\nWe are looking for individuals to help us plan and organize the activities for this event. \nIf you are interested in helping out either before the event or on the day\, please sign up here to get more information. \nSchedule of Activities\n(Tentative schedule; all times are Pacific Time) \n\n\n\n\nTime\nActivity\n\n\n9.30–9:45\nRegistration\n\n\n9:45–10:15\nWelcome and Icebreaker Game\n\n\n10:15–11:00\nUndergraduate and Graduate Student Panel \n\nPriansh A. (Undergraduate\, Psychology)\nRoxana Darvishi (Master’s Student\, Statistics)\nJuliet Fowler (Master’s Student\, Computational Neuroscience)\nKathleen Moody (Undergraduate\, Criminology)\nKun Peng (Andy) Zhang (Undergraduate\, Computer Science)\n\n\n\n\n11:00–11:15\nBreak\n\n\n11:15–12:30\nInteractive Activities\n\n\n12:30–1:15\nLunch\n\n\n 1:15–2:00\nCareer Panel \n\nKristen Bystrom (Data Scientist\, Yelp)\nYing Li (Analyst\, Statistics Canada)\nHa Dinh (Senior Data Scientist\, Shopify)\nLin Zhang (Assistant Professor\, SFU)\nDuong Vu (Senior Data Scientist\, MasterCard)\n\n\n\n\n2:00–2:15\nWrap-up\n\n\n2:15–3.45\nSFU Campus Tour\n\n\n\n\nAbout Florence Nightingale Day\nFlorence Nightingale Day was launched in the U.S. in 2018. Since then\, it has become an international one-day initiative with in-person activities for local high school students organized at colleges and universities and virtual activities for students from all over the world. In the U.S.\, it has been celebrated at a number of institutions\, including Ohio State University\, Harvard University\, and the University of Texas at Dallas. In Canada it has been celebrated at Simon Fraser University\, the University of Toronto (co-sponsored by CANSSI Ontario)\, the Université de Montréal\, and the University of New Brunswick. CANSSI is a major co-sponsor and co-organizer of Florence Nightingale Day together with the Caucus for Women in Statistics and the American Statistical Association. It’s part of our developing effort to attract under-represented and disadvantaged high school students to study statistical sciences. Our vision is to expand Florence Nightingale Day to become a national event involving high school students across Canada. \nIn 2025\, CANSSI will support events at multiple locations\, including Simon Fraser University\, the University of Alberta\, the University of Toronto\, York University\, and the Université de Montréal. Our goal is to expand the number of sites each year. Check out these photos from the Florence Nightingale Day 2024 celebrations organized by CANSSI and the hosting universities. \nFor an international list of upcoming Florence Nightingale Day celebrations\, visit this page.
URL:https://canssi.ca/events/fnday-2025-at-sfu/
LOCATION:Simon Fraser University (Halpern Centre)\, Burnaby\, British Columbia\, V5A 1S6\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/FN-Day-2025-at-SFU-EN-3.png
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BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250410T130000
DTEND;TZID=America/Toronto:20250410T140000
DTSTAMP:20260530T152956
CREATED:20250415T222513Z
LAST-MODIFIED:20250416T010447Z
UID:27659-1744290000-1744293600@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science Webinar: Astronomy & Cosmic Emulation
DESCRIPTION:Date: Thursday\, April 10\, 2025\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nAbout the Presentation\nJoin us for the second NISS-CANSSI Collaborative Data Science Webinar: Astronomy & Cosmic Emulation. This webinar explores the role of statistical modelling and computational techniques in advancing our understanding of the universe. Featuring Kelly Renee Moran (Los Alamos National Laboratory) and Katrin Heitmann (Argonne National Laboratory)\, the presentation will highlight how statistical emulation accelerates complex astrophysical simulations\, enabling researchers to study cosmic structures more efficiently. Key statistical concepts discussed include iterative space-filling designs\, statistical smoothing techniques\, and Gaussian process based emulation and calibration. Emily Casleton (Los Alamos National Laboratory) will moderate the session\, guiding an engaging conversation at the intersection of data science\, astronomy\, and high-performance computing. \nREGISTER ON ZOOM \n\nAbout the Speakers\nKelly Renee Moran is an applied statistician at Los Alamos National Laboratory (LANL)\, where she applies statistical modelling and computational tools to tackle complex problems across multiple scientific disciplines. From astrophysics to epidemiology\, Moran’s expertise helps researchers extract meaningful insights from their data. Moran joined LANL’s Statistical Sciences Group in 2020 after working intermittently with the lab over five years. Her early interest in applied statistics led her to LANL as an undergraduate at Clemson University\, where she engaged with the lab’s epidemiology group. She later pursued a PhD in statistics at Duke University with a Department of Energy Computational Science Graduate Fellowship (DOE CSGF)\, completing multiple research practicums at Los Alamos before joining full-time. Her research spans a wide array of topics. She has contributed to epidemiology by analyzing internet search data to forecast global disease trends and\, during the COVID-19 pandemic\, studied how viral variants spread based on demographics and immunity factors. In space science\, Moran worked with data from NASA’s Interstellar Boundary Explorer (IBEX) satellite to determine whether different particle detection events could stem from a common heliosphere signal. Additionally\, she has played a key role in cosmological modelling\, developing an emulator to predict the matter power spectrum from large-scale simulations\, enabling researchers to study cosmic structure more efficiently. Beyond research\, Moran has also contributed to occupational safety at LANL by automating systems for monitoring employee health and hazard exposure. She is an active member of LANL’s Computational\, Computer\, and Statistical Sciences (CCS) division\, where she helps foster professional development and collaboration among early-career researchers. Moran’s interdisciplinary approach and problem-solving mindset make her an invaluable contributor to LANL’s mission\, advancing knowledge across scientific frontiers through data-driven discovery. \nKatrin Heitmann is a Physicist and Computational Scientist at Argonne National Laboratory in the High Energy Physics Division. She is also a Senior Associate for the Kavli Institute for Cosmological Physics at the University of Chicago and a member of NAISE at Northwestern University. Before joining Argonne\, Katrin was a staff member at Los Alamos National Laboratory. Her research currently focuses on computational cosmology\, in particular on trying to understand the causes for the accelerated expansion of the universe. She is responsible for large simulation campaigns with HACC (Hardware/Hybrid Accelerated Cosmology Code) and for the tools in the associated analysis library\, CosmoTools. Katrin is a member of several major astrophysical surveys that aim to shed light on this question and was until recently the spokesperson for the LSST Dark Energy Science Collaboration. Her research interests include cosmology; study of dark energy\, dark matter\, and inflation; and high-performance computing. \nAbout the Moderator\nEmily Casleton is a Statistician in the Statistical Sciences Group at Los Alamos National Laboratory (LANL) and was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015\, Emily has routinely collaborated with seismologists\, nuclear engineers\, physicists\, geologists\, chemists\, and computer scientists on a wide variety of cool data-driven projects. Most recently\, her research focus has been on testing and evaluating large AI models. She holds a BS in Mathematics and Political Science from Washington & Jefferson College\, 2003; an MS in Statistics from West Virginia University\, 2006; and a PhD in Statistics from Iowa State University. \nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session will feature two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees will gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars will not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-apr2025/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSS-CoLab-Apr-10-EN-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250320T130000
DTEND;TZID=America/Toronto:20250320T140000
DTSTAMP:20260530T152956
CREATED:20250219T210850Z
LAST-MODIFIED:20250319T234607Z
UID:27308-1742475600-1742479200@canssi.ca
SUMMARY:NISS-CANSSI Collaborative Data Science Webinar: Changing Climate\, Changing Data—A Journey of Statisticians and Climate Scientists
DESCRIPTION:Date: Thursday\, March 20\, 2025\nTime: 1:00–2:00 p.m. Eastern time\nLocation: On Zoom \nJoin Us\nJoin us for the NISS-CANSSI Collaborative Data Science Webinar Series: Changing Climate\, Changing Data—A Journey of Statisticians and Climate Scientists. This webinar features Claudie Beaulieu (University of California\, Santa Cruz) and Rebecca Killick (Lancaster University)\, with moderation by Emily Casleton (Los Alamos National Laboratory). The discussion will explore how climate change impacts society and the critical role of statistical methods in understanding climate variability and trends. The speakers will highlight their research on whether global warming is accelerating\, share insights into their collaboration\, and discuss challenges in publishing statistical work in environmental science. Ethical considerations in climate data analysis will also be examined. Don’t miss this opportunity to gain valuable perspectives at the intersection of statistics and climate science! \nPresentation Abstract\nClimate change is impacting our society in many different ways. Scientifically and societally\, we need to accurately estimate the magnitude of these changes to inform and lead societal adaptation and mitigation to ongoing and future change. Understanding the underlying mechanisms of these changes necessitates robust characterization and quantification of observed and simulated data. This talk will introduce our ongoing work in quantifying climate change and variability\, centred around the current debate as to whether global warming is accelerating\, or not. We will touch on how our collaboration started and evolved\, the pros and cons of publishing statistical work in environmental journals\, and ethical quandaries. \nREGISTER ON ZOOM \n\nAbout the Speakers\nDr. Claudie Beaulieu is an Assistant Professor of Ocean Sciences at the University of California (UC)\, Santa Cruz\, whose groundbreaking work in environmental data science has earned her a Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF). This prestigious award supports her integrated research and education program\, which focuses on understanding climate variability and climate change by leveraging data science techniques. Dr. Beaulieu’s research addresses the critical need to comprehend the drivers of oceanic and climatic variability and change. Her work tackles the challenge of analyzing the increasingly complex environmental data made available through advances in climate and ocean monitoring\, observational platforms\, and Earth system modelling. By applying statistical and machine learning methods\, she aims to maximize insights from observational data and model simulations. Dr. Beaulieu earned her PhD in Water Sciences from the Institut National de la Recherche Scientifique Centre Eau Terre et Environnement in Quebec. She conducted postdoctoral research in atmospheric and oceanic sciences at Princeton University and was a lecturer in the School of Ocean and Earth Science at the University of Southampton before joining the UC Santa Cruz faculty in 2018. Through her research\, education\, and outreach efforts\, Dr. Beaulieu is shaping the future of climate science and environmental data analysis\, while inspiring and equipping the next generation of environmental scientists. \nRebecca Killick is a Senior Lecturer in Statistics at Lancaster University and joined the Centre for Health Informatics\, Computing\, and Statistics (CHICAS) in March 2021 following a discipline-hopping award from the Engineering and Physical Sciences Research Council (EPSRC). After completing their PhD in 2012 within the Mathematics and Statistics department\, Rebecca was a Postdoctoral Research Associate before obtaining a lectureship in Mathematics and Statistics in 2013. Alongside her departmental role\, Rebecca is Head of the Lancaster University Women’s Network and Furness College Advisor. In 2019 they were the first UK recipient of the “Young Statistician of the Year” award from the European Network for Business and Industrial Statistics\, which recognizes the work of young people in introducing innovative methods\, promoting the use of statistics\, and/or successfully using it in daily practice. Rebecca sees their research as a feedback loop\, being inspired by problems in real-world applications\, creating novel methodology to solve those problems and then feeding these back into the problem domain. Their primary research interests lie in development of novel methodology for the analysis of univariate and multivariate nonstationary time series models. This covers many topics including developing models\, model selection\, efficient estimation\, diagnostics\, clustering\, and prediction. Rebecca is highly motivated by real-world problems and has worked with data in a range of fields including Bioinformatics\, Energy\, Engineering\, Environment\, Finance\, Health\, Linguistics\, and Official Statistics. Rebecca is passionate about ensuring the availability and accessibility of research in the form of open-source software. As part of this\, they advocate to the statistical community the importance of recognition of research software as an academic output\, are Co-Editor in Chief of the Journal of Statistical Software\, and are a member of the rOpenSci statistical software peer review board. \nAbout the Moderator\nEmily Casleton is currently the Deputy Group Leader of the statistical sciences group at the Los Alamos National Laboratory (LANL)\, but was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a postdoc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015\, Emily has routinely collaborated with seismologists\, nuclear engineers\, physicists\, geologists\, chemists\, and computer scientists on a wide variety of cool data-driven projects. Most recently\, she has been the PI of a data analytics project under the NA-22 venture MINOS; co-organizer of the invited CCS-6 seminar series; and co-chair of CoDA\, the conference that brought her to LANLA a decade ago. She holds a BS in Mathematics and Political Science from Washington & Jefferson College\, 2003; an MS in Statistics from West Virginia University\, 2006; and a PhD in Statistics from Iowa State University\, 2014. \nAbout the NISS-CANSSI Collaborative Data Science Webinar Series\nIn an era where data transcends traditional boundaries\, fostering interdisciplinary collaboration has never been more crucial. Together with the National Institute of Statistical Sciences (NISS)\, we are proud to present the NISS-CANSSI Collaborative Data Science webinar series dedicated to showcasing data scientists and domain scientists from diverse scientific fields who collaborate to advance science. This initiative celebrates the power of collaboration\, demonstrating how the fusion of data science with various disciplines can drive innovation\, solve complex problems\, and push the frontiers of knowledge beyond the realm of statistics. \nEach session will feature two speakers: a data scientist and a subject matter expert from another domain who have successfully partnered to achieve impactful results. Through their shared experiences and insights\, attendees will gain a deeper understanding of the collaborative processes that bridge gaps between different scientific landscapes. These seminars will not only highlight successful partnerships but also provide a platform for exchanging ideas\, methodologies\, and best practices that inspire new collaborations.
URL:https://canssi.ca/events/niss-canssi-cds-webinar-session-1/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSS-CoLab-Mar-20-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250308T100000
DTEND;TZID=America/Vancouver:20250308T153500
DTSTAMP:20260530T152956
CREATED:20250219T034550Z
LAST-MODIFIED:20250303T200442Z
UID:27324-1741428000-1741448100@canssi.ca
SUMMARY:Spring 2025 UBC/SFU Joint Statistics Seminar: Lessons Learned from Developing and Maintaining Open-Source Software
DESCRIPTION:Date: Saturday\, March 8\, 2025\nTime: 10:00 a.m.–3:35 p.m. Pacific time\, followed by a social hour\nLocation: UBC Earth Sciences Building\, Room 5104\, 2207 Main Mall\, Vancouver\, B.C. \nCANSSI is proud to co-sponsor the Spring 2025 UBC/SFU Joint Statistics Seminar. \nThe UBC/SFU Joint Statistics Seminar is jointly hosted by the graduate students of the University of British Columbia (UBC) Department of Statistics and the Simon Fraser University (SFU) Department of Statistics and Actuarial Science. The Spring 2025 event is the second of two events taking place in the 2024/2025 academic year. The Fall 2024 event was organized by graduate students from SFU\, and the Spring 2025 event is organized by graduate students from UBC. Over its 20-year history\, the event has offered Statistics and Actuarial Science graduate and undergraduate students at both schools an opportunity to network with their peers and to attend accessible talks about the research work of their fellow students and faculty. \nThe Spring 2025 event includes talks given by six students (three from UBC and three from SFU)\, followed by a presentation on “Lessons Learned from Developing and Maintaining Open Source Software” by Professor Geoff Pleiss (Assistant Professor\, Department of Statistics\, UBC). \nThe day will also include multiple opportunities for networking and socializing. Note that this event is in-person only. \nRegistration\nTo express your interest in presenting or to register for the event\, visit the event web page. \nSchedule\n(All times are Pacific Time) \n\n\n\nTime\nActivity\n\n\n10:00–10:30 a.m.\nBreakfast\n\n\n10:30–10:35 a.m.\nWelcome Message\n\n\n10:35–11:00 a.m.\nSpeaker 1: Agam Sanghera (UBC)\n\n\n11:05–11:30 a.m.\nSpeaker 2: George Thomas (SFU)\n\n\n11:35 a.m.–12:00 noon\nSpeaker 3: Seren Lee (UBC)\n\n\n12:00 noon–1:00 p.m.\nLunch\n\n\n 1:00–1:25 p.m.\nSpeaker 4: Hashan Peiris (SFU)\n\n\n1:30–1:55 p.m.\nSpeaker 5: Rachel Lobay (UBC)\n\n\n2:00–2:25 p.m.\nSpeaker 6: Hasitha Jayaneththi (SFU)\n\n\n2:25–2:35 p.m.\nBreak\n\n\n2:35–3:35 p.m.\nProfessor Geoff Pleiss (UBC)\nLessons Learned from Developing and Maintaining Open-Source Software\n\n\n3:40 p.m.\nNetworking and Drinks at Browns Crafthouse UBC\n\n\n\n 
URL:https://canssi.ca/events/ubc-sfu-joint-statistics-seminar/
LOCATION:University of British Columbia\, Earth Sciences Building (ESB) 5104\, Vancouver\, British Columbia\, V6T 1Z4\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/UBCSFU-Seminar-Spring-2025-Alt-EN.png
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BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20241115T074500
DTEND;TZID=America/Vancouver:20241115T153000
DTSTAMP:20260530T152956
CREATED:20241008T190459Z
LAST-MODIFIED:20241113T210201Z
UID:26263-1731656700-1731684600@canssi.ca
SUMMARY:CANSSI Showcase 2024
DESCRIPTION:Date: Friday\, November 15\, 2024\nTime: 7:45 a.m.–3:30 p.m. Pacific time\nLocation: Online \nConnect with the Community\nThe CANSSI Showcase is an annual celebration of the work being done by Canadian statistical sciences researchers\, postdoctoral fellows\, and students—and a chance to connect with Canada’s statistical sciences community. \nCANSSI Showcase 2024 will be held virtually on Friday\, November 15\, 2024. It will be a wonderful opportunity for you to: \n\nHear about the work being done within Canada’s statistical sciences community\nShowcase your research (especially if you are a graduate student\, postdoc\, or early career faculty member)\nDiscover career opportunities\nGain a better understanding of CANSSI’s activities\nLearn about the different ways CANSSI can support your work\n\nWe invite you to join us for a full schedule of exciting events\, including a keynote presentation by Hongtu Zhu (University of North Carolina at Chapel Hill)\, a panel discussion with distinguished Canadian and U.S. panellists\, lightning talks by students\, postdoctoral fellows\, and faculty members\, and presentations by CANSSI-funded researchers. \nYou’ll leave with new inspiration\, deeper connections\, and a richer understanding of what is happening across Canada. \nRegister to Showcase Your Research\nWhether you are a student\, a postdoctoral fellow\, or a faculty member\, the Showcase offers you an opportunity to present your work to a national audience through a 12-minute online lightning talk. Register as a presenter to save your spot. \nSpace is limited and presentation slots will be filled on a first-come\, first-served basis. We encourage you to register early if you hope to present. \nREGISTER AS A PRESENTER \nRegister to Attend\nDon’t miss this chance to connect with Canada’s statistical sciences community. You’ll learn about current research and expand your professional network. \nREGISTER FOR GENERAL ATTENDANCE \nShowcase Schedule\n\n\n\nTime (PST)\nActivity\n\n\n7:45–8:00\nOpening and Welcome: Introduction of Speaker\n\n\n8:00–9:00\nKeynote Lecture: “Revolutionizing Medical Data Analysis: Uniting AI and Statistics for Breakthroughs and Challenges”\nSpeaker: Hongtu Zhu (University of North Carolina at Chapel Hill)\nSee the keynote abstract and speaker bio below\n\n\n9:00–9:15\nBreak\n\n\n9:15–10:45\nPanel Discussion: “The Role of Statistics in Data Science\, Machine Learning\, and AI”\nModerator: Bei Jiang\nPanellists:\n \n\nAlexandre Bouchard (University of British Columbia)\nLinglong Kong (University of Alberta)\nAurélie Labbe (HEC Montréal)\nBhramar Mukherjee (Yale School of Public Health)\nHongtu Zhu (University of North Carolina at Chapel Hill)\n\nSee the panel description below\n\n\n10:45–11:00\nBreak\n\n\n11:00–12:15\nCANSSI Short Talks \n\nMai Ghannam (University of Ottawa): “Block Maxima Methods in Heavy-tailed Heteroskedastic Models”\nKehinde Olobatuyi (University of Victoria): “Multi-event Dynamic Capture-Recapture Model for Big Data: Estimating Undetected COVID-19 Cases in British Columbia\, Canada”\nAlex Sharp (University of British Columbia): Title to come\nRishikesh Yadav (HEC Montréal): “Sparse Spatiotemporal Dynamic Generalized Linear Models for Inference and Prediction of Bike Counts”\n\n\n\n\n12:15–12:30\nBreak\n\n\n12:30–3:15\nLightning Talks \n\nElham Afzali (University of Manitoba)\nPankaj Bhagwat (University of Alberta)\nIlhem Bouderbala (Université Laval)\nForough Fazeli Asl (University of Alberta)\nRajitha Rajitha Senanayake (McMaster University)\nDivya Sharma (York University)\nZheng Yu (University of Calgary)\n\n\n\n\n3:15–3:30\nWrap-up\n\n\n\n\nKeynote Lecture\nRevolutionizing Medical Data Analysis: Uniting AI and Statistics for Breakthroughs and Challenges\n \nAbstract: This talk provides an insightful overview of integrating artificial intelligence (AI) and statistical methods in medical data analysis. It is structured into three key sections: \n\nIntroduction to Medical Image Data Analysis: This section sets the stage by outlining the fundamentals and significance of medical image analysis in healthcare\, charting its evolution and current applications.\nState-of-the-Art AI Applications and Statistical Challenges: Here\, we explore the impact of AI\, particularly deep learning\, on medical imaging\, and address the accompanying statistical challenges\, such as data quality and model interpretability.\nOpportunities for Statisticians: The final section highlights the critical role of statisticians in refining AI applications in medical imaging\, focusing on opportunities for advancing algorithmic accuracy and integrating statistical rigour. The talk aims to demonstrate the crucial synergy between AI and statistics in enhancing medical data analysis\, emphasizing the evolving challenges and the vital contributions of statisticians in this domain.\n\nAbout the Keynote Speaker \nDr. Hongtu Zhu is a tenured professor of biostatistics\, statistics\, radiology\, computer science\, and genetics at University of North Carolina at Chapel Hill. He was DiDi Fellow and Chief Scientist of Statistics at DiDi Chuxing between 2018 and 2020 and was Endowed Bao-Shan Jing Professorship in Diagnostic Imaging at MD Anderson Cancer Center between 2016 and 2018. He is an internationally recognized expert in statistical learning\, medical image analysis\, precision medicine\, biostatistics\, artificial intelligence\, and big data analytics. He has been an elected Fellow of the American Statistical Association and the Institute of Mathematical Statistics since 2011. He received an established investigator award from Cancer Prevention Research Institute of Texas in 2016 and received the INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice in 2019. He has published more than 340 papers in top journals including Nature\, Science\, Cell\, Nature Genetics\, PNAS\, AOS\, JASA\,Biometrika\, and JRSSB\, as well as 55+ conference papers in top conferences including NeurIPS\, AAAI\, KDD\, ICDM\, ICML\, MICCAI\, and IPMI. \nPanel Discussion\nThe Role of Statistics in Data Science\, Machine Learning\, and AI\nAbout the Panellists\n\n\n\n\nAbout Alexandre Bouchard: Alexandre Bouchard is a Professor of Statistics at the University of British Columbia. He received his PhD in computer science from the University of California\, Berkeley. His research focuses on computational Bayesian methods and applications in cancer genomics and phylogenetics.\n\n\n\nAbout Linglong Kong: Dr. Linglong Kong is a professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. He holds a Canada Research Chair in Statistical Learning and a Canada CIFAR AI Chair. He is a fellow of the American Statistical Association (ASA) and a fellow of the Alberta Machine Intelligence Institute (AMII). His publication record includes more than 100 peer-reviewed articles in top journals such as AOS\, JASA\, and JRSSB as well as top conferences such as NeurIPS\, ICML\, ICDM\, AAAI\, and IJCAI. Dr. Kong currently serves as associate editor of the Journal of the American Statistical Association\, the Annals of Applied Statistics\, the Canadian Journal of Statistics\, and Statistics and its Interface. Additionally\, Dr. Kong was a member of the Executive Committee of the Western North American Region of the International Biometric Society\, chair of the ASA Statistical Computing Session program\, and chair of the webinar committee. He served as a guest editor of the Canadian Journal of Statistics and Statistics and its Interface\, associate editor of the International Journal of Imaging Systems and Technology\, guest associate editor of Frontiers of Neurosciences\, chair of the ASA Statistical Imaging Session\, and member of the Statistics Society of Canada’s Board of Directors. He is interested in functional and neuroimaging data analysis\, statistical machine learning\, robust statistics and quantile regression\, trustworthy machine learning\, and artificial intelligence in smart health.\n\n\n\nAbout Aurélie Labbe: Aurélie Labbe is a professor in the Department of Decision Sciences and holder of the FRQ-IVADO Chair in Data Science. She specializes in large-scale data analysis. With a master’s degree in Statistics from Université de Montréal and a PhD in the same discipline from the University of Waterloo\, she has spent over 15 years developing statistical tools for big data with applications in the fields of genomics\, neuroscience\, and biostatistics. Since joining HEC Montréal in 2016\, her research interests have largely focused on the analytical challenges generated by data from intelligent transportation systems. Aurélie Labbe is also active in the community\, as she has been appointed scientific co-director of IVADO since October 2023\, and director of the StatLab at the Centre de Recherche en Mathématiques (CRM) since July 2023.\n\n\n\nAbout Bhramar Mukherjee: Professor Bhramar Mukherjee is currently appointed as Anna M.R. Lauder Professor of Biostatistics and Professor of Chronic Disease Epidemiology at the Yale School of Public Health (YSPH). Professor Mukherjee serves as the inaugural Senior Associate Dean of Public Health Data Science and Data Equity at YSPH. She holds a secondary appointment in the Department of Statistics and Data Science and is affiliated with the MacMillan Center and the Institute for the Foundations of Data Science. She serves on the Yale Cancer Center Director’s cabinet. \nDr. Mukherjees’s research interests span statistical methods for analyzing electronic health records\, gene-environment interaction studies\, data integration\, data equity\, shrinkage estimation\, and the analysis of environmental mixtures. Collaboratively\, she contributes to areas such as cancer\, cardiovascular diseases\, reproductive health\, exposure science\, and environmental epidemiology. With over 390 publications in statistics\, biostatistics\, medicine\, and public health\, Professor Mukherjee is globally recognized for her research contributions in integrating genetic\, environmental and health outcome data. She has served as the Principal Investigator on methodology grants funded by the National Science Foundation (NSF) and the National Institutes of Health (NIH).\n\n\n\nAbout Hongtu Zhu: See the Keynote Lecture section above.\n\n\n\n 
URL:https://canssi.ca/events/canssi-showcase-2024/
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Showcase-Keynote-2024.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20240209T093000
DTEND;TZID=America/Vancouver:20240209T163000
DTSTAMP:20260530T152956
CREATED:20230927T201044Z
LAST-MODIFIED:20240408T190242Z
UID:23637-1707471000-1707496200@canssi.ca
SUMMARY:Florence Nightingale Day 2024
DESCRIPTION:Florence Nightingale Day 2024 at Simon Fraser University is coming up! This one-day event is part of an international celebration that gives high school students\, especially those from traditionally under-represented groups\, a chance to explore educational and career opportunities in statistical sciences. It is named after Florence Nightingale\, the widely known founder of modern nursing who was also a ground-breaking statistician credited with inventing the pie chart. \nIn British Columbia\, Florence Nightingale Day 2024 will be co-hosted on Friday\, February 9\, by the Canadian Statistical Sciences Institute (CANSSI) and Simon Fraser University (SFU)’s Department of Statistics and Actuarial Science. The event will take place at SFU’s Burnaby campus and will include fun hands-on activities\, panel discussions featuring university students and professionals\, and opportunities for participants to talk to university students about their experiences and interest in studying statistics. The day has three goals: \n\nTo give high school students an understanding of the strong benefits of studying statistics for their future career paths\nTo give high school students a glimpse of what studying statistics in university is like\nTo promote diversity in statistics and data science by encouraging and inspiring high school students from all communities to explore statistics\n\nHigh school students will hear what it’s like to study and work in different areas of statistical sciences\, and they will have the opportunity to ask questions and talk directly with statistics students and professionals. The day will also give them a chance to explore the uses of statistics through engaging games and activities. Lunch is free for all participating students and teachers! \nWhat Happens at Florence Nightingale Day\nWhat does the event look like? Check out these photos from Florence Nightingale Day 2023. \n\n\n\nClose to 30 high school students attended the first CANSSI-sponsored Florence Nightingale Day at Simon Fraser University on February 3\, 2023.\n\n\n\n\n\nStatistics is already more diverse than many other STEM fields. One goal of Florence Nightingale Day is to build on that strength.\n\n\n\n\n\nA number of SFU students shared their experiences with statistics. From left: Yuxin Liu\, Nirodha Epasinghege Dona\, Tom Xie\, Sarah Zwiep\, and Ryan Smith.\n\n\n\n\n\nDerek Bingham\, chair of SFU’s Department of Statistics & Acturial Science\, welcomed students and moderated a career panel.\n\n\n\n\n\nMembers of the career panel described opportunities in statistics and data science. From left: Owen Ward (SFU)\, Lucas Wu (Zelus Analytics)\, Shannon Lo (Statistics Canada)\, Hayley Boyce (Slalom)\, and Kristen Bystrom (Yelp).\n\n\n\n\n\nStudents rotated through group activities\, including the famous Monty Hall Problem.\n\n\n\n\n\nThese students were glued to the screen—in a good way!\n\n\n\n\n\nThe atmosphere was high-energy throughout the group activities …\n\n\n\n\n\n… and the discussion was lively despite the masks.\n\n\n\n\n\nAre those answers? There seems to be some disagreement!\n\n\n\n\n\nBecky Lin\, a lecturer in SFU’s Department of Statistics & Actuarial Science\, played a central role in organizing the event.\n\n\n\n\n\nCANSSI scientific coordinator Nathan Ngongo was a key member of the organizing team.\n\n\n\n\n\nThe first-time event was a huge success\, thanks also to the enthusiastic support of SFU student volunteers\, identifiable by their blue shirts and friendly smiles.\n\n\nHow to Participate\nSpace is limited for this event\, and we can’t guarantee that everyone who signs up will be able to participate. Please use the links below to express your interest\, and we will follow up to confirm your participation. \nHigh School Teachers\nIf you would like to bring your class or a group of students to Florence Nightingale Day 2024\, we can make it easy by providing transportation and a free lunch for you and your students. \nTo express your interest\, please fill out this form and we’ll contact you. \nStudents\nIf you would like to attend on your own\, please sign up here and we’ll contact you. \nVolunteers\nWe are looking for individuals to help us plan and organize the activities for this event. \nIf you are interested in helping out either before the event or on the day\, please sign up here to get more information. \nSchedule of Activities\n(Tentative schedule; all times are Pacific Time) \n\n\n\n\nTime\nActivity\n\n\n9.30–9:45\nRegistration\n\n\n9:45–10:15\nWelcome and Icebreaker Game\n\n\n10:15–11:00\n\nUndergraduate and Graduate Student Panel \n\nSonia Dosanjh (Undergraduate\, Political Science\, with minor in Social Data Analytics)\nJuliet Fowler (Master’s Student\, Computational Neuroscience)\nValerie Kistrina (Undergraduate\, Computer Science\, with minor in Statistics)\nKathleen Moody (Undergraduate\, Criminology)\nHashan Peiris (PhD Candidate\, Actuarial Science)\nRyan Smith (Undergraduate\, Psychology)\n\n\n\n\n11:00–11:15\nBreak\n\n\n11:15–12:30\nInteractive Activities\n\n\n12:30–1:15\nLunch\n\n\n 1:15–2:00\n\nCareer Panel \n\nHayley Boyce (Data Scientist\, Slalom)\nKristen Bystrom (Data Scientist\, Yelp)\nKimberly Kroetch (Data Scientist\, SMT (SportsMEDIA Technology Corp.))\nYing Li (Analyst\, Statistics Canada)\nLin Zhang (Professor\, Statistics and Actuarial Science\, Simon Fraser University)\n\n\n\n\n2:00–2:15\nWrap-up\n\n\n2:15–3.45\nSFU Campus Tour\n\n\n\n\nAbout Florence Nightingale Day\nFlorence Nightingale Day was launched in the U.S. in 2018. Since then\, it has become an international one-day initiative with in-person activities for local high school students organized at colleges and universities and virtual activities for students from all over the world. In the U.S.\, it has been celebrated at a number of institutions\, including Ohio State University\, Harvard University\, and the University of Texas at Dallas. In Canada it has been celebrated at Simon Fraser University and at the University of Toronto (co-sponsored by CANSSI Ontario). CANSSI is a major co-sponsor and co-organizer of Florence Nightingale Day together with the Caucus for Women in Statistics and the American Statistical Association. It’s part of our developing effort to attract under-represented and disadvantaged high school students to study statistical sciences. Our vision is to expand Florence Nightingale Day to become a national event involving high school students across Canada. \nIn 2024\, CANSSI will support events at Simon Fraser University\, the University of Toronto\, and potentially other universities. Our goal is to expand the number of sites each year. Check out these photos from the Florence Nightingale Day 2023 celebration organized by CANSSI and the Department of Statistics and Actuarial Science at SFU. \nFor an international list of upcoming Florence Nightingale Day celebrations\, visit this page.
URL:https://canssi.ca/events/fnday-2024/
LOCATION:Simon Fraser University (Halpern Centre)\, Burnaby\, British Columbia\, V5A 1S6\, Canada
CATEGORIES:CANSSI National,EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/FN-Day-2024-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20231117T074500
DTEND;TZID=America/Vancouver:20231117T153000
DTSTAMP:20260530T152956
CREATED:20230926T200902Z
LAST-MODIFIED:20240114T014818Z
UID:23659-1700207100-1700235000@canssi.ca
SUMMARY:CANSSI Showcase 2023
DESCRIPTION:Watch the Videos\nThis event is past\, but recordings of the sessions are available online: \n\nKeynote lecture (see description below)\nPanel discussion (see description below)\nShort talks (four presenters; see descriptions below)\nLightning talks (15 presenters; see descriptions below)\nConclusion (including announcement of meme contest winners)\n\nConnect with the Community\nThe CANSSI Showcase is an annual celebration of the work being done by CANSSI-supported researchers\, postdoctoral fellows\, and students across Canada. \nCANSSI Showcase 2023 will be held virtually on Friday\, November 17. It will be a wonderful opportunity for you to: \n\nConnect and network with Canada’s statistical sciences community\nShowcase your research (especially if you are a graduate student\, postdoc\, or younger faculty member)\nDiscover career opportunities\nGain a better understanding of CANSSI’s activities\nLearn about the different ways CANSSI can support your work\n\nWe invite you to join us for a full schedule of exciting events\, including a keynote presentation by Sallie Ann Keller (U.S. Census Bureau\, University of Virginia)\, a panel discussion with distinguished Canadian and U.S. panellists\, lightning talks by students\, postdoctoral fellows\, and faculty members\, and presentations by CANSSI-funded researchers. \nYou’ll leave with new inspiration\, deeper connections\, and a richer understanding of what is happening across Canada. \nRegister to Showcase Your Research\nWhether you are a student\, a postdoctoral fellow\, or a faculty member\, the Showcase offers you an opportunity to present your work to a national audience through an 8-minute online lightning talk. Register as a presenter to save your spot. \nSpace is limited and presentation slots will be filled on a first-come\, first-served basis. We encourage you to register early if you hope to present. \nREGISTER AS A PRESENTER (closed) \nRegister to Attend\nDon’t miss this chance to connect with Canada’s statistical sciences community. You’ll learn about current research and expand your professional network. \nREGISTER FOR GENERAL ATTENDANCE (closed) \nShowcase Schedule\n\n\n\nTime (PST)\nActivity\n\n\n7:45–8:00\nOpening and Welcome: Introduction of Speaker\n\n\n8:00–9:00\nKeynote Lecture: “Evolving a Data Enterprise to Support Relevant\, Timely\, and Equitable Statistical Products”\nSpeaker: Sallie Ann Keller (U.S. Census Bureau and University of Virginia)\nSee the keynote abstract and speaker bio below\n\n\n9:00–9:15\nBreak\n\n\n9:15–10:45\nPanel Discussion: “The Role of Statistics for Public Good and Good Governance”\nModerator: Meredith Franklin\nPanellists:\n• Josée Bégin (Statistics Canada)\n• F. Jay Breidt (NORC at the University of Chicago)\n• Dave Campbell (Carleton University\, Bank of Canada)\n• Sallie Ann Keller (U.S. Census Bureau)\nSee the panel description below\n\n\n10:45–11:00\nBreak\n\n\n11:00–12:15\nCANSSI Short Talks\nModerator: Audrey Béliveau | Presenter bios\n1. Antonio Herrera Martin (University of Toronto): “Rare Events in Astronomy with Repeating FRBs”\n2. Gracia Dong (University of Toronto | University of Victoria): “Using Capture-Recapture with Data Extracts from Healthcare Records to Estimate Population Sizes of Vulnerable Populations – Applications and Data Quality Issues”\n3. Benjamin Bloem-Reddy (University of British Columbia): “Non-parametric Hypothesis Tests for Distributional Group Symmetry”\n4. Tianyu Guan (Brock University): “Comparison of Individual Playing Styles in Soccer”\n\n\n12:15–12:30\nBreak\n\n\n12:30–3:15\nLightning Talks\nModerator: Saman Muthukumarana | Presenter bios\n1. Alysha Cooper (University of Guelph): “Modelling Benthic Compositions Using Regularized DM Regression”\n2. Ander Diaz-Navarro (Ontario Institute for Cancer Research): “In Silico Generation of Synthetic Cancer Genomes Using Deep Learning Algorithms”\n3. Arthur Chatton (Université de Montréal): “Personalized Dynamic Super Learning”\n4. Carlotta Pacifici (HEC Montréal | University of Bologna): “Dynamic Tail Risk Estimation Using Extreme Value Theory: An Application to the S&P 500 Index”\n5. Cong Jiang (Université de Montréal): “Efficient and Doubly Robust Estimation of COVID-19 Vaccine Effectiveness Under the Test-negative Design”\n6. Di Meng (Wilfrid Laurier University): “Short Selling Incentives and Contingent Convertible Securities”\n7. Harsh Kumar (University of Toronto): “Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health”\n8. Lara Maleyeff (McGill University): “Bayesian Model Averaging for the Identification of Tailoring Variables in Adaptive Factorial Designs”\n9. Luke Hagar (University of Waterloo): “Scalable Power Curves with Targeted Hypercube Sampling”\n10. Nikola Surjanovic (University of British Columbia): “Exploration-agnostic Geometric Ergodicity of Non-reversible Parallel Tempering”\n11. Richard Yan (Simon Fraser University): “A Generalized Phase I/II Dose Optimization Trial Design with Multi-categorial and Multi-graded Outcomes”\n12. Skyepaphora Griffith (Queen’s University): “Spectrogram Smoothing for Estimation of the Evolutionary Power Spectra of Uniformly Modulated Processes”\n13. Surani Matharaarachchi (University of Manitoba | Government of Manitoba): “Long COVID Prediction in Manitoba Using Clinical Notes Data: A Machine Learning Approach”\n14. Xiaoting Li (University of British Columbia): “Estimation of Conditional Value-at-Risk Using Copulas”\n16. Yuan Bian (University of Western Ontario): “A Unified Framework of Analyzing Missing Data and Variable Selection Using Regularized Likelihood”\n\n\n3:15–3:30\nMeme Contest Winners and Wrap-up\nMeme Judges: Rafal Kulik and Léo Raymond-Belzile\n\n\n\n\nKeynote Lecture\nEvolving a Data Enterprise to Support Relevant\, Timely\, and Equitable Statistical Products \nAbstract: This is an exciting time to be part of official statistics. There is growing demand for statistical products that traditional surveys alone cannot address. Stakeholders want timelier\, more accurate\, more granular\, and differently structured information about people\, places\, and the economy than ever before. New data sources and data science innovations allow us to meet those demands. In today’s digital era\, massive amounts of data are generated as we go about our daily lives. This volume of data generated every day\, through commercial and personal transactions and the management of federal\, state\, and local programs\, continues to grow exponentially. This provides an incredible opportunity to revolutionize how we capture and use data to develop relevant products. Instead of limiting ourselves to the data our surveys produce\, we can flip the paradigm to design products based on what data users need. To do this we must integrate our survey data with other data sources. This presentation will share how the U.S. Census Bureau plans to re-envision its data enterprise based on a statistical product–first approach. This approach includes eliciting the purposes and uses our data are to support\, collaborating with internal and external data users to develop the products using ALL our data assets\, and then embracing varying access modes for statistical product dissemination to support stakeholder needs at all levels of data acumen. The research and enabling technologies to support this journey has begun! This work will modernize and transform our official statistical infrastructure. \nAbout the Keynote Speaker \nDr. Sallie Ann Keller is chief scientist and associate director of the U.S. Census Bureau’s Research and Methodology Directorate. She also holds an endowed distinguished professorship in biocomplexity and faculty appointments in the School of Medicine\, Department of Public Health Services; School of Engineering and Applied Science\, Department of Engineering Systems and Environment; and School of Data Science at the University of Virginia (UVA). \nAs chief scientist\, Keller leads the Research and Methodology Directorate’s research centers\, each devoted to domains of investigation important to the future of social and economic statistics. The directorate collaborates with teams across the U.S. Census Bureau and with researchers worldwide to develop innovative scientific solutions and advances to ensure the Census Bureau remains a leader in economic and social measurement. \nKeller is a nationally recognized research scientist with expertise in social and decision informatics\, statistical underpinnings of data science\, and data access and confidentiality. She is a leading voice in creating the science of all data and advancing this research across disciplines to benefit society. \nHer prior positions include director of the Social and Decision Analytics Division within UVA’s Biocomplexity Institute and Initiative; professor of statistics and director of the Social and Decision Analytics Laboratory within the Biocomplexity Institute of Virginia Tech; academic vice president and provost at the University of Waterloo; director of the Institute for Defense Analyses Science and Technology Policy Institute; the William and Stephanie Sick Dean of Engineering at Rice University; head of the Statistical Sciences group at Los Alamos National Laboratory; professor of statistics at Kansas State University; and Statistics Program director at the National Science Foundation. \nKeller is an elected member of the U.S. National Academy of Engineering. She has served as a member of the National Academy of Sciences Board on Mathematical Sciences and Their Applications and the Committee on National Statistics\, and as chair of the Committee on Applied and Theoretical Statistics. She is a fellow of the American Association for the Advancement of Science\, an elected member of the International Statistics Institute\, and a fellow and past president of the American Statistical Association. Keller earned her B.S. and M.S. in mathematics from the University of South Florida and her Ph.D. in statistics from Iowa State University. \nPanel Discussion\nThe Role of Statistics for Public Good and Good Governance \nDescription: Statistics provides the essential framework for developing and evaluating evidence-informed public policy and governance operations. This panel will focus on emerging pressures and opportunities on statistics related to the public good as well as ways in which young statisticians can become involved in this area through research and careers. \nAbout the Panellists \nAbout Josée Bégin: Josée Bégin has a master’s degree in mathematics and statistics (MSc) from the University of Ottawa. She started her career at the Canada Revenue Agency in 1994 before joining Statistics Canada in 2002\, where she gained experience in overseeing large and complex statistical programs. Josée became the Assistant Chief Statistician of the Social\, Health and Labour Statistics Field in January 2023. \nThe Social\, Health and Labour Statistics Field provides accurate\, timely and relevant information across a range of social topics to decision makers at all levels of government\, non-governmental organizations\, researchers and the Canadian public. Its portfolio includes a number of large survey and administrative data programs\, such as the Centre for Population Health Data; the Canadian Centre for Justice and Community Safety Statistics; the Centre for Gender\, Diversity and Inclusion Statistics; and the Centre for Labour Market Information. This field is also home to Canadian census content expertise. \nHer favourite hobbies include yoga and reading. \nAbout F. Jay Breidt: F. Jay Breidt\, PhD\, is a Senior Fellow in the Department of Statistics and Data Science at NORC at the University of Chicago. He is also Professor Emeritus and past Chair of the Department of Statistics at Colorado State University. His expertise is mathematical statistics\, with interests that include survey sampling\, time series\, nonparametric regression\, and uncertainty quantification for complex scientific models. Breidt has an extensive record of refereed publications and has presented over 130 invited short courses\, conference talks\, and academic seminars. Breidt has been an associate editor for seven different journals and Reviews Editor for the Journal of the American Statistical Association. He has served on six review committees for the National Academy of Sciences and has served two terms on the Federal Economic Statistics Advisory Committee. He currently chairs the Census Scientific Advisory Committee for the US Census Bureau. Breidt is an elected Fellow in both the American Statistical Association and the Institute of Mathematical Statistics. \nAbout Dave Campbell: Dr. Dave Campbell is a Full Professor in the School of Mathematics and Statistics and the School of Computer Science at Carleton University. Academically\, he runs a collaborative team researching inferential algorithms at the intersections of statistics with machine learning\, computing\, and applied mathematics to solve problems inspired by industry and government collaborations. He has co-authored discussion papers in Bayesian Analysis and the Journal of the Royal Statistical Society (Series B) and been awarded over $3.5 million in research grants.  \nDave’s career path maintains a theme of Data Science leadership. He spent two years leading a Data Science team at the Bank of Canada in projects relating to cybersecurity\, forecasting banknote demand\, understanding drivers of inflation\, ensuring data privacy\, and more. Before moving to Ottawa in 2019\, Dave was a Professor at Simon Fraser University\, where he led the creation of their BSc in Data Science. He was the inaugural President of the Data Science and Analytics Section of the Statistical Society of Canada and was a co-organizer of the Vancouver Learn Data Science Meetup.  \nFind him on LinkedIn: https://www.linkedin.com/in/drdavecampbell/  \nAbout Sallie Ann Keller: See the Keynote Lecture section above.
URL:https://canssi.ca/events/showcase-2023/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Showcase-2023-General.png
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20230803
DTEND;VALUE=DATE:20230805
DTSTAMP:20260530T152956
CREATED:20230427T194128Z
LAST-MODIFIED:20230503T191810Z
UID:22303-1691020800-1691193599@canssi.ca
SUMMARY:2nd CANSSI-NISS Health Data Science Workshop
DESCRIPTION:Overview\nNowadays\, statisticians and health data scientists actively work together on the frontier of biological\, medical\, and public health research. The transdisciplinary collaboration not only develops the modern foundations of Health Data Science but also accelerates the pace of scientific discovery and innovation. \nThe 2nd CANSSI-NISS Health Data Science Workshop will be held on August 3–4\, 2023\, at the University of Waterloo in Waterloo\, Ontario. The two-day workshop brings statisticians and health data scientists from the U.S. and Canada together to explore current approaches and new challenges for learning Big Data in Health Data Science. \nThe workshop consists of two keynote presentations (with Charmaine Dean\, University of Waterloo\, and Eric J. Tchetgen Tchetgen\, University of Pennsylvania)\, three invited sessions\, a poster competition for students and new researchers\, and a banquet/dinner on Day 1. \nThe themed invited sessions will explore current approaches and new challenges in: \n\nStatistical Methods for Precision Health\nCausal Inference for Big Health Data\nAI and Health Data Science\n\nRegistration\nDiscounted registration fees for this workshop will apply to the following registrants: \n\nCANSSI National Institutional Members registrants\nNISS Affiliate registrants\nStudents currently enrolled at a university\n\nFor more details and to register\, visit the conference web page. \n 
URL:https://canssi.ca/events/2nd-canssi-niss-health-data-science-workshop/
LOCATION:University of Waterloo\, 200 Ring Rd\, Waterloo\, Ontario\, N2L 3G1\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/2nd-CANSSI-NISS-Health-Data-Science-Workshop-1.png
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20230802
DTEND;VALUE=DATE:20230806
DTSTAMP:20260530T152956
CREATED:20230414T185750Z
LAST-MODIFIED:20230503T213048Z
UID:22068-1690934400-1691279999@canssi.ca
SUMMARY:23rd Meeting of New Researchers in Statistics and Probability
DESCRIPTION:The 23rd Meeting of New Researchers in Statistics and Probability will take place from August 2 to 5\, 2023\, at the University of Toronto. It is co-sponsored by the Institute of Mathematical Statistics (IMS)\, the National Science Foundation (NSF)\, the University of Toronto\, and the Canadian Statistical Sciences Institute (CANSSI). \nThe conference is designed to promote networking and interaction among new researchers in the fields of statistics\, biostatistics\, and probability\, including those who expect to hold tenure-track positions in the near future. \nAnyone who has received a PhD in or after 2016\, or expects to receive a PhD by the end of 2023\, is eligible to attend\, although participation is by invitation only\, based upon poster or speed-talk submissions submitted by Monday\, April 24. \nAttendees will present their research through a brief expository talk and/or poster\, and have the chance to mingle throughout the day. There will be longer talks by senior researchers\, and panels on various topics such as publishing\, grant applications\, collaboration\, and mentoring. The conference covers a broad range of topics in statistics\, applied statistics\, and some probability. \nVisit the conference web page for details and the online application form.
URL:https://canssi.ca/events/meeting-of-new-researchers-2023/
LOCATION:University of Toronto\, 700 University Ave\, Toronto\, Ontario\, M5G 1X6\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/IMS-New-Researchers-Conference-V3.png
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20230711
DTEND;VALUE=DATE:20230714
DTSTAMP:20260530T152956
CREATED:20230323T192843Z
LAST-MODIFIED:20230515T215134Z
UID:21741-1689033600-1689292799@canssi.ca
SUMMARY:IASE 2023: Fostering Learning of Statistics and Data Science
DESCRIPTION:Are you interested in “Fostering Learning of Statistics and Data Science”? \nThat’s the theme of IASE 2023\, a satellite conference being organized by the International Association for Statistical Education (IASE) and the International Association for Statistical Computing (IASC) as a lead-up to the 64th World Statistics Congress in Ottawa. \nCANSSI is a co-sponsor of the three-day event\, which will be hosted by the Department of Statistical Sciences at the University of Toronto from July 11 to 13. Those who cannot attend in person may participate virtually. \nThe conference will feature more than 40 presentations and 35 posters\, including three exciting keynote speakers: Chris Wild (University of Auckland\, New Zealand)\, Shingai Manjengwa (Vector Institute for Artificial Intelligence\, Toronto)\, and Jürgen Symanzik (Utah State University). \nRegister now\nEarly-bird registration at reduced rates is open until April 30. \nFor more information and to register\, visit the IASE 2023 website.
URL:https://canssi.ca/events/iase-2023/
LOCATION:University of Toronto\, 700 University Ave\, Toronto\, Ontario\, M5G 1X6\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/IASE-2023-FINAL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20230616T100000
DTEND;TZID=America/Vancouver:20230616T110000
DTSTAMP:20260530T152956
CREATED:20200511T151320Z
LAST-MODIFIED:20230618T041641Z
UID:22441-1686909600-1686913200@canssi.ca
SUMMARY:2023 CANSSI Town Hall
DESCRIPTION:WATCH THE VIDEO RECORDING \nDOWNLOAD THE TOWN HALL PRESENTATION SLIDES (PDF) \nIf you’ve been meaning to explore what CANSSI can offer you\, the 2023 CANSSI Town Hall is for you. \nThe Town Hall will take place on Friday\, June 16\, from 10:00 to 11:00 a.m. PT on Zoom. \nIt is open to all members of the statistical sciences community. If you are interested in receiving a fast-paced overview of CANSSI’s programs\, activities\, and plans for the future\, we invite you to join your colleagues from across Canada for this session. \nREGISTER HERE FOR THE CANSSI TOWN HALL. (Registration closed) \nOnce you have registered\, you will receive a Zoom link for the session via email. \nAgenda\n\nOverview of CANSSI’s budget and core financial commitments.\nUpdates about CANSSI programs\n       a. Graduate Student Enrichment Scholarships changes\n       b. Version 2.0 of Research for Social Good\n       c. Mentoring program\n       d. Community consultation about EDI\nCurrent identity of CANSSI\n\nNOTE: If you are a CANSSI representative for your university\, note that the Town Hall will occur immediately after the 2023 CANSSI Annual General Meeting (AGM)\, which will take place from 9:30 to 10:00 a.m. PT\, also on Zoom. CANSSI representatives will receive materials and a Zoom link for the AGM via email.
URL:https://canssi.ca/events/2023-town-hall/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/2023-Town-Hall-REGISTER-BELOW-1.png
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BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20230607T120000
DTEND;TZID=America/Vancouver:20230607T140000
DTSTAMP:20260530T152956
CREATED:20230302T201042Z
LAST-MODIFIED:20230308T192417Z
UID:21634-1686139200-1686146400@canssi.ca
SUMMARY:Mentoring 101: How to Get What You Need to Thrive in the Academy
DESCRIPTION:As part of its Equity\, Diversity\, and Inclusion (EDI) program\, CANSSI regularly organizes EDI workshops and training sessions for the statistical sciences community. \nWe invite you to join us for this two-hour online workshop developed by the National Center for Faculty Development & Diversity and led by Dr. Joy Gaston Gayles\, professor of higher education at North Carolina State University. \nREGISTER ON EVENTBRITE \nProgram\n\nDo you have a reliable and strong network of mentors?\nAre you struggling to cultivate mentoring relationships?\nDo you know the difference between a mentor and a sponsor?\nAre you moving to a new stage of your career and wondering how to find new mentors and sponsors that are appropriate to the next level?\n\nTraditional ideas about mentoring often leave faculty feeling that something is missing in their professional development. In this workshop\, we challenge the conventional wisdom about faculty mentoring and present a new framework to help you re-imagine how mentoring works. All participants will map their current mentoring network\, identify the pressing areas of need that are not being met\, and create a plan to expand their existing mentoring network. \nWorkshop Leader\n\nJoy Gaston Gayles\nProfessor of Higher Education\nNorth Carolina State University \nJoy Gaston Gayles\, Ph.D.\, is a professor of higher education at North Carolina State University. She has established an international reputation for her research on intercollegiate athletics in higher education. Dr. Gayles is well known for her research on women and underrepresented people of color in STEM fields. In 2022\, DIVERSE magazine named Dr. Gayles one of 25 influential women leading higher education. In addition\, she has published more than 50 refereed articles and book chapters on issues of diversity and equity in postsecondary education. Dr. Gayles participated in NCFDD’s Faculty Success Program in 2014 and now serves as a faculty success coach and campus workshop facilitator. She has coached over 100 faculty participants through the FSP program and has facilitated over five dozen campus workshops. Dr. Gayles loves to travel and make memories with her teenagers. As a former student-athlete\, she is a sports and exercise enthusiast.
URL:https://canssi.ca/events/mentoring101/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National,EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/Banner-Mentoring-101.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20230509T153000
DTEND;TZID=America/Vancouver:20230510T163000
DTSTAMP:20260530T152956
CREATED:20230405T044153Z
LAST-MODIFIED:20230414T033311Z
UID:22055-1683646200-1683736200@canssi.ca
SUMMARY:Eric Joel Tchetgen Tchetgen Will Speak at the 2023 Distinguished Lecture Series in Statistical Sciences
DESCRIPTION:CANSSI and CANSSI Ontario are excited to present Eric Joel Tchetgen Tchetgen as the guest speaker for this year’s Distinguished Lecture Series in Statistical Sciences at the University of Toronto. Dr. Tchetgen Tchetgen will present two talks: \n\nAn (un)Holy Union: Causal Inference\, Semiparametric Statistics and Machine Learning in the Age of Data Science (May 9\, 3:30–4:30 p.m. ET)\nSingle Proxy Control (May 10\, 3:30–4:30 p.m. ET)\n\nVisit the event web page for abstracts of the talks and to register for in-person or virtual attendance. \nAbout Eric Joel Tchetgen Tchetgen\nDr. Tchetgen Tchetgen is the inaugural Luddy Family President’s Distinguished Professor in the Department of Statistics at The Wharton School of the University of Pennsylvania as well as an Adjunct Professor of Biostatistics and Epidemiologic Methods at the Harvard Chan School. Dr. Tchetgen Tchetgen has distinguished himself as one of the leading young biostatisticians and epidemiologic methodologists in the world\, having made numerous influential contributions to the development and application of statistical methods for missing data\, causal inference\, and semiparametric regression in social\, genetic and infectious disease epidemiology. In addition to his myriad of research accomplishments\, Dr. Tchetgen Tchetgen is a talented and inspiring teacher and mentor who has published well over 200 papers in top statistical\, epidemiological and medical journals\, produced an impressive record of grant funding\, and has generously and tirelessly served the statistical profession\, both nationally and internationally. He is a hardworking\, creative\, and well-respected leader\, and through his statistical talent\, has dedicated his career to advancing public health. He was awarded the inaugural Rousseeuw Prize for Statistics in 2022 for his contributions to causal inference and its applications in Medicine and Public Health.
URL:https://canssi.ca/events/eric-joel-tchetgen-tchetgen-2023/
CATEGORIES:CANSSI National,CANSSI Ontario
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DTSTART;TZID=America/Vancouver:20230504T120000
DTEND;TZID=America/Vancouver:20230504T140000
DTSTAMP:20260530T152956
CREATED:20220913T163703Z
LAST-MODIFIED:20230508T032355Z
UID:19261-1683201600-1683208800@canssi.ca
SUMMARY:Microaggressions: They Aren’t Being Too Sensitive
DESCRIPTION:As part of its Equity\, Diversity\, and Inclusion (EDI) program\, CANSSI regularly organizes EDI workshops and training sessions for the statistical sciences community\, often in partnership with Academic Impressions (opens in a new tab). \nWe invite you to join us for this two-hour online workshop led by Sandra Miles of Academic Impressions. \n  \nWATCH THE WEBINAR RECORDING\n(Available until June 4\, 2023; use this passcode: #1$3uLH%) \nDOWNLOAD THE PRESENTATION SLIDES\nDOWNLOAD THE LIST OF PRIVILEGED AND MARGINALIZED GROUPS \n  \nProgram\nMicroaggressions refer to any language or behaviour that causes unintended offense to a member of a marginalized group. During this session a list of more than 20 categories that can make a person a member of a marginalized or privileged group will be presented for the purpose of clarifying the various ways we all can work to be more intentional in our interactions. The nature of a microaggression is that it is causing offense without intending to\, so the focus will not be on bullying\, but on understanding the difference between intent vs impact. \nObjectives: \n\nIdentify and define microaggressions\nDevelop skills to effectively name\, respond to\, and prevent microaggressions in personal and professional settings\nUnderstanding the role of privilege and implicit bias in recognizing and interrupting microaggressions\nOpportunities to practice deconstructing microaggressions\n\nWorkshop Leader\nSandra Miles\, PhD\nHead of Practice for Diversity/Equity/Inclusion\, Academic Impressions\n \nSandra has spent most of the last two decades serving as a leader and administrator in higher education. Specifically\, she has had extensive experience in managing crisis\, strategic planning\, developing leadership programs\, working with persons with disabilities\, mediating disputes\, and serving as a Dean of Students\, Chief Student Affairs Officer\, Chief Diversity Officer\, and Deputy Title IX Coordinator. In 2022\, Sandra joined Academic Impressions full-time as the Head of Practice for Diversity\, Equity\, and Inclusion\, due to her experience with the organization as a subject-matter expert who facilitated trainings and workshops in higher-ed\, as well as to her passion for making DEI concepts resonate for individuals from all walks of life. \nSandra completed her doctoral work at Florida State University in 2012\, earning a Ph.D. in Higher Education Administration. She also completed her bachelor’s and master’s degrees at the University of Central Florida. In addition to her career and educational achievements\, Sandra is on the editorial board for EVOLVE Magazine – First Coast Edition; is a former Chair of the NASPA Center for Women Board; is a former National Director of the Black Female Development Circle\, Inc.; and is the current President of the Palm Coast-Flagler County Alumnae Chapter of Delta Sigma Theta Sorority\, Inc.
URL:https://canssi.ca/events/microaggressions/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National,EDI
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DTSTART;TZID=America/Toronto:20230217T130000
DTEND;TZID=America/Toronto:20230217T163000
DTSTAMP:20260530T152956
CREATED:20230127T002544Z
LAST-MODIFIED:20230127T002728Z
UID:21472-1676638800-1676651400@canssi.ca
SUMMARY:Best Practice in Ethical Data Analysis
DESCRIPTION:This virtual workshop\, which is presented by the Centre de recherches mathématiques (CRM) StatLab and supported by CANSSI\, will showcase best practices in thoughtful and ethical handling of demographic data. A particular focus will be common questions that arise in the analysis of variables on race\, ethnicity\, sexuality\, and disability. These include the challenges presented by small cell sizes\, considerations of inequality in outcomes\, and discussion of how statistical analyses can be used to raise questions about such inequities in society. The workshop will focus on methodological and applied concerns\, giving attendees immediately useful and actionable advice. \nThe event organizers are Dr. Erica Moodie (McGill University) and Dr. Michael Wallace (University of Waterloo). Speakers include Dr. Rubab Arim and Dr. Evelyne Bougie (Statistics Canada\, Social Analysis and Modelling Division)\, Dr. AJ Lowik (Centre for Gender and Sexual Health Equity)\, Dr. Irene Chen (University of California\, Berkeley and San Francisco)\, and Dr. Emma Pierson (Jacobs Technion-Cornell Institute). \nFor additional information about the program and to register\, visit the event page on the CRM website.
URL:https://canssi.ca/events/best-practice-in-ethical-data-analysis/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National
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DTSTART;TZID=America/Vancouver:20230203T093000
DTEND;TZID=America/Vancouver:20230203T151500
DTSTAMP:20260530T152956
CREATED:20220901T222021Z
LAST-MODIFIED:20230112T012650Z
UID:19024-1675416600-1675437300@canssi.ca
SUMMARY:Florence Nightingale Day 2023
DESCRIPTION:Florence Nightingale is widely known as the founder of modern nursing\, but she was also a ground-breaking statistician who is credited with inventing the pie chart. \nFlorence Nightingale Day is an international celebration that invites high school students\, especially those from traditionally under-represented groups\, to follow in her footsteps by exploring studies and careers in statistics and data sciences. \nIn British Columbia\, Florence Nightingale Day 2023 will be co-hosted on Friday\, February 3\, by us—the Canadian Statistical Sciences Institute (CANSSI)—and Simon Fraser University (SFU)’s Department of Statistics and Actuarial Science. \nThe event will take place at SFU’s Burnaby campus and will include fun hands-on activities\, panel discussions by university students and professionals\, and opportunities for participants to talk to university students about their experiences and interest in studying statistics. \nCareer panelists will speak about their experiences working in different areas of statistical sciences\, potential career paths\, and higher education in the field. Students will have the opportunity to explore the field and have their questions answered during the session through lively conversations. The day will mix engaging activities with friendly discussions to offer a prospective future in statistical and data sciences. Lunch will also be provided for the students and teachers attending. \nThe day has three goals: \n\nTo give high school students an understanding of the strong benefits of studying statistics for their future career paths\nTo give high school students a glimpse of what studying statistics in university is like\nTo promote diversity in statistics and data science by encouraging and inspiring high school students from all communities to explore statistics\n\nSchedule of Activities\n(All times are Pacific Time) \n\n\n\n\nTime\nActivity\n\n\n9.30–10.00\nRegistration\n\n\n10:00–10:15\nWelcome Talk\n\n\n10:15–11:00\nUndergraduate and Graduate Student Panel \n\nNirodha Epasinghege Dona\, PhD student\, statistics\n\nYuxin Liu\, undergraduate\, statistics\nRyan Smith\, undergraduate\, psychology\nTom Xie\, undergraduate\, molecular biology and biochemistry and computer science\nSarah Zwiep\, undergraduate\, computer science with minor in statistics\n\n\n\n\n11:00–11:15\nBreak\n\n\n11:15–12:30\nInteractive Activities\n\n\n12:30–1:15\nLunch\n\n\n 1:15–2:00\nCareer Panel \n\nHayley Boyce\, data scientist\, Slalom\nKristen Bystrom\, data scientist\, Yelp\nShannon Lo\, data scientist\, Statistics Canada\, Text Analytics and Digitalization Section\nOwen Ward\, statistics professor\, Simon Fraser University\nLucas Wu\, data scientist\, Zelus Analytics\n\n\n\n\n2:00–2:15\nWrap-up\n\n\n2:15–3.15\nSFU Campus Tour\n\n\n\n\nFor Students\nInterested in participating as a student? Sign up here if you would like to attend on your own. \nFor Teachers\nIf you would like to bring a class of students to this event\, we can make it easy by providing transportation and free lunch for your students. \nInterested in participating as a teacher? Sign up here and we’ll get in touch. \nFor Volunteers\nWe are looking for individuals to help us plan and organize the activities for this event. If you can help us either before the event or on the day\, please let us know. There are lots of ways to get involved. \nInterested in participating as a volunteer? Sign up here to get more information. \nAbout Florence Nightingale Day\nFlorence Nightingale Day was launched in the U.S. in 2018. Since then\, it has become an international one-day event with in-person activities for local high school students organized at colleges and universities and virtual activities for students from all over the world. In the U.S.\, it was celebrated at Ohio State University\, Harvard University\, and the University of Texas at Dallas in October 2022. It will be celebrated in British Columbia for the first time in February 2023. \nCANSSI is a major co-sponsor and co-organizer of Florence Nightingale Day together with the Caucus for Women in Statistics and the American Statistical Association. It’s part of our developing effort to attract under-represented and disadvantaged high school students to study statistical and data sciences. Our vision is to expand Florence Nightingale Day to become a national event involving high school students across Canada. \nIn February 2023\, CANSSI will support events at Simon Fraser University and the University of Toronto. Our goal is to expand the number of sites each year. \nCheck out these photos from the Florence Nightingale Day celebration organized by CANSSI Ontario and the Department of Statistical Sciences at the University of Toronto on April 9\, 2022.
URL:https://canssi.ca/events/fn-day-2023/
LOCATION:Simon Fraser University (Halpern Centre)\, Burnaby\, British Columbia\, V5A 1S6\, Canada
CATEGORIES:CANSSI National,EDI
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DTSTART;TZID=America/Vancouver:20230202T110000
DTEND;TZID=America/Vancouver:20230202T123000
DTSTAMP:20260530T152956
CREATED:20230127T035654Z
LAST-MODIFIED:20230207T231852Z
UID:21492-1675335600-1675341000@canssi.ca
SUMMARY:van Eeden Seminar: The Four Pillars of Machine Learning
DESCRIPTION:The van Eeden seminar is presented each year by the University of British Columbia’s Department of Statistics. The invited speaker is a prominent statistician chosen by the department’s graduate students. This year’s vitual seminar is sponsored by CANSSI and features Dr. Kevin Patrick Murphy\, a research scientist at Google. \nFor more information and to register for the seminar\, visit the event page on the UBC statistics department website. \nWATCH THE VIDEO RECORDING OF THIS SEMINAR ON YOUTUBE \nPresentation Abstract\n“I will present a unified perspective on the field of machine learning research\, following the structure of my recent book\, Probabilistic Machine Learning: Advanced Topics (https://probml.github.io/book2). In particular\, I will discuss various models and algorithms for tackling the following four key tasks\, which I call the “pillars of ML”: prediction\, control\, discovery and generation. For each of these tasks\, I will also briefly summarize a few of my own contributions\, including methods for robust prediction under distribution shift\, statistically efficient online decision making\, discovering hidden regimes in high-dimensional time series data\, and for generating high-resolution images.”
URL:https://canssi.ca/events/van-eeden-seminar-machine-learning/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/Banner-Van-Eeden-Seminar.png
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DTSTART;TZID=America/Vancouver:20230125T100000
DTEND;TZID=America/Vancouver:20230125T120000
DTSTAMP:20260530T152956
CREATED:20220818T032805Z
LAST-MODIFIED:20230207T223344Z
UID:17808-1674640800-1674648000@canssi.ca
SUMMARY:Cultural Humility: A Framework to Mitigate Personal Bias & Techniques to Build Greater Capacity
DESCRIPTION:As part of its Equity\, Diversity\, and Inclusion (EDI) program\, CANSSI regularly organizes EDI workshops and training sessions for the statistical sciences community\, often in partnership with Academic Impressions. \nWe invite you to join us for this two-hour online workshop led by Sana Loue of Case Western Reserve University School of Medicine. \n  \nWATCH THE WEBINAR RECORDING\n(Use this passcode to access the recording: Canssi-Pims_01.25.23) \nDOWNLOAD THE PRESENTATION SLIDES \n  \nLearning Objective\nParticipants will learn techniques and strategies to increase their own cultural humility and how to apply these techniques and strategies to mitigate the ways that bias shows up in day to day interactions. \nProgram\nWe all have biases that show up in our interactions and perceptions of others. But these biases can be problematic when they are used unconsciously or consciously to judge\, misinterpret\, or limit our interactions with others. How often do you pause and reflect on your social interactions and ask yourself “What did I assume about this person that was not accurate”? By reflecting and holding ourselves accountable for how biases show up in our interactions\, we not only encourage our own personal growth\, but we also create opportunity to fully understand another person’s lived experience. During the first half of this workshop\, you will understand the root cause of your biases and develop a practice that helps mitigate bias in your interactions with others. \nWe’ll use the time in the second half to learn and practice techniques that you can incorporate into your daily routine to help you become a more culturally conscious and sensitive individual. Simply put\, you’ll learn how to integrate the often competing responses from your head and heart. These techniques will help you become more aware of your own biases and how they get triggered in your interactions with others\, maintain better self control in the moment when your biases are triggered\, and cultivate more meaningful growth in yourself as well as in your relationships with others. \nSection 1: Understanding Bias & Cultural Humility\nFirst\, our instructor will help you understand personal bias including how you develop and sustain your biases over time. Next\, you will learn the definition of cultural humility and apply this framework to explore your own biases through two exercises. \nSection 2: Identifying Barriers to Developing Cultural Humility\nWe will discuss and identify possible barriers that prevent you from applying cultural humility in your interactions with others\, including: \n\nRecognizing your personal triggers\nForgiving yourself and others for missteps\nBelieving that you or others can change\n\nSection 3: Applying Cultural Humility\nOur instructor will guide you through a facilitated exercise that will help you foster cultural humility in your daily routine to identify\, analyze\, challenge\, and mitigate your personal biases. \nSection 4: Techniques to Increase Cultural Humility\nYou’ll be introduced to each of the following techniques: journaling\, body scans\, accountability partners\, and mindfulness meditation. You’ll have the opportunity to apply them to a case study and discuss how they can be used to help you reflect and modulate your thoughts and behaviors. \nWorkshop Faculty\nSana Loue\, J.D.\, Ph.D.\, M.P.H.\, M.S.S.A.\, M.A.\, LISW\, CST-T\, AVT\nProfessor in the Department of Bioethics at Case Western Reserve University School of Medicine \nDr. Loue holds secondary appointments in Psychiatry and Global Health at the School of Medicine and in Social Work at the Mandel School of Applied Social Sciences at CWRU. She served as the medical school’s inaugural Vice Dean for Faculty Development and Diversity from 2012–2020. Dr. Loue has been trained in law (JD)\, epidemiology (PhD)\, medical anthropology (PhD)\, social work (MSSA)\, secondary education (MA)\, public health (MPH) and theology (MA) and is ordained as an interfaith minister through the New Seminary in New York and as a Modern Rabbi\, through Rabbinical Seminary International\, also in New York. Her empirical research has focused on HIV risk and prevention\, severe mental illness\, family violence\, and research ethics. \nRead Sana’s full bio here.
URL:https://canssi.ca/events/cultural-humility/
LOCATION:Queen’s University\, 127 Jeffery Hall\, 48 University Avenue\, Queen's University\, Kingston\, Ontario\, K7L 3N8\, Canada
CATEGORIES:CANSSI National
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