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DTSTART;TZID=America/Toronto:20250918T130000
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DTSTAMP:20260511T023622
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SUMMARY:NISS-CANSSI Collaborative Data Science: Statistical Ecology
DESCRIPTION:Date: Thursday\, September 18\, 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\, focusing on “Statistical Ecology.” \nPresentation Abstract\nThis session brings together leading researchers working at the intersection of statistics\, ecology\, and data science to discuss cutting-edge methodologies and applications in ecological monitoring\, spatial analysis\, and population modelling. \nThis virtual webinar will feature Dr. Laura Cowen (University of Victoria) and Dr. Patrick D. O’Hara (ECCC-CWS\, Institute of Ocean Sciences)\, whose work integrates statistical innovation with real-world ecological challenges. Moderated by Dr. Saman Muthukumarana (University of Manitoba)\, the discussion will provide insights into collaborative\, data-intensive research driving ecological understanding and conservation efforts in Canada and beyond. \nREGISTER ON ZOOM \nAbout the Speakers\nDr. Laura L.E. Cowen is a Professor of Statistics in the Department of Mathematics and Statistics at the University of Victoria and currently serves as the Acting Dean of Science. She joined the university in 2005 as an Assistant Professor and has since held various leadership roles\, including Associate Chair of her department and the inaugural Associate Dean of Research for the Faculty of Science. Dr. Cowen specializes in ecological statistics\, with a focus on capture-recapture methodologies used to estimate population parameters such as survival and abundance. Her research encompasses a wide range of applications\, including studies on human populations\, fisheries\, aquaculture\, and seabirds. She has collaborated with scientists across disciplines—ecologists\, fisheries scientists\, microbiologists\, and sociologists—to address complex ecological and public health problems. Her academic journey began with extensive field research on seabirds in British Columbia and Alaska. She earned her Master of Mathematics in Biostatistics from the University of Waterloo and her PhD in Statistics from Simon Fraser University\, focusing on developing models to estimate the population size of hidden populations. Beyond her research\, Dr. Cowen is committed to equity\, diversity\, and inclusion (EDI) in academia. As Associate Dean of Research\, she initiated the Faculty of Science’s EDI Council and has been instrumental in launching programs to support underrepresented groups in science\, such as the formation of a campus chapter of the American Indian Science and Engineering Society (AISES) and the establishment of Indigenous student travel scholarships. Dr. Cowen’s contributions to statistical science and her dedication to fostering inclusive research environments have made her a respected leader in her field. \nDr. Patrick D. O’Hara is with Environment and Climate Change Canada\, based at the Institute of Ocean Sciences (Sidney\, B.C.). His current interests include spatially explicit modelling of risk of impact associated with human activities and pollution. This modelling includes predictive modelling of marine bird and mammal distributions based on movement and at-sea observation data\, which is used primarily to identify characteristics of key foraging habitats that these organisms rely on to fuel migration\, feed chicks\, or simply survive winter. Dr. O’Hara has recently begun exploring multi-event modelling techniques with Dr. Laura Cowen to increase precision of population trends for marine species at risk. Patrick co-supervises undergraduate and graduate students and postdoctoral fellows in the Departments of Mathematics and Statistics (Dr. Laura Cowen) and Biology (Dr. Francis Juanes).\n\nAbout the Moderator\nDr. Saman Muthukumarana is a Professor and Head of the Department of Statistics at the University of Manitoba\, where he also serves as Director of the Data Science Nexus. He joined the department as an Assistant Professor in July 2010\, was promoted to Associate Professor with tenure in 2016\, and became a full Professor in 2022. Dr. Muthukumarana received his BSc Honours Special Degree in Statistics from the University of Sri Jayewardenepura\, Sri Lanka. He went on to complete an MSc in Statistics at Simon Fraser University in 2007. His MSc work was recognized as a discussed paper in the Canadian Journal of Statistics. He continued his graduate studies under the supervision of Dr. Tim Swartz\, completing his PhD in June 2010\, with research focused on Bayesian methods and applications. His doctoral work has been published in the Canadian Journal of Statistics and the Australian & New Zealand Journal of Statistics. His primary research interests are centred on Bayesian methods and computation for complex models\, with a strong emphasis on multidisciplinary applications. He has developed novel methodologies to support modelling and inference on non-standard and complex data types\, enabling innovative analyses across various domains including social networks\, health studies\, sports analytics\, customer and user behaviour\, and environmental and ecological studies. Dr. Muthukumarana has secured over $8.4 million in research funding independently and collaboratively from numerous sources. These include the Natural Sciences and Engineering Research Council of Canada (NSERC)\, Mitacs Globalink and Accelerate\, Manitoba Institute of Child Health (MICH)\, Fisheries and Oceans Canada\, Canadian Institutes of Health Research (CIHR)\, the Canadian Statistical Sciences Institute (CANSSI)\, Research Manitoba\, and several internal and interdisciplinary grants from the University of Manitoba. \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-sep2025/
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/NISS-CANSSI-CoLab-Sep-18-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250909T100000
DTEND;TZID=America/Toronto:20250909T160000
DTSTAMP:20260511T023622
CREATED:20250517T012540Z
LAST-MODIFIED:20250903T175642Z
UID:27809-1757412000-1757433600@canssi.ca
SUMMARY:CANSSI Quebec Postdoc Day 2025
DESCRIPTION:Join Us\nOn Tuesday\, September 9\, 2025\, CANSSI Quebec will host Postdoc Day 2025 at Concordia University in Montreal. \nCANSSI Quebec’s Postdoc Day is an annual celebration of work being done by postdoctoral fellows in statistical sciences at Quebec universities. It’s a great opportunity for the statistical sciences community to meet Quebec-based postdoctoral fellows doing statistics-centred research. The event will feature research presentations by postdocs from across the province\, followed by a reception. \nWe hope you’ll be able to join us either in person or on Zoom! \nSee a blog post about last year’s Postdoc Day. \nEvent Details and Registration\nDate: Tuesday\, September 9\, 2025\nTime: 10:00 a.m. to 4:00 p.m.\nLocation: Concordia University\, 1400 De Maisonneuve W\, Montreal\, LB 921.04 (J.W. McConnell Building) and on Zoom* \nREGISTER ON EVENTBRITE \n*The Zoom link will be sent to all registrants via email. \nPresent Your Work\nIf you are a postdoctoral fellow in statistical sciences at a CANSSI member university in Quebec and would like to present your research (35-minute talk followed by 10-minute Q&A)\, send your CV along with the title and abstract of your talk to incass-quebec@incass.ca by Friday\, August 1 (extended deadline). \nSchedule\nThe event will take place in the Conference Room of the Department of Mathematics and Statistics of Concordia University (LB 921.04). \n9:00 | Welcoming Remarks \n9:05–9:50 | Presentation 1 | Mariia Samoilenko (Université Laval) \n9:50–10:35 | Presentation 2 | Zinsou Max Debaly (Université de Sherbrooke) \n10:35–11:20 | Presentation 3 | Rinel Foguen Tchuendom (HEC Montréal) \n11:20–12:05 | Presentation 4 | Hui Shen (McGill University) \n12:05–13:00 | Lunch Break \n13:00–13:45 | Presentation 5 | Sébastien Jessup (University of Waterloo; previously Concordia University) \n13:45–14:30 | Presentation 6 | Rachel Morris (Concordia University) \n14:30–15:15 | Presentation 7 | Marouane Il Idrissi (Université du Québec à Montréal) \n15:15–16:00 | Presentation 8 | Sophie Morin (Polytechnique Montréal) \n16:00 | Closing Remarks
URL:https://canssi.ca/events/canssi-quebec-postdoc-day-2025/
LOCATION:Concordia University\, 1400 De Maisonneuve Boulevard W\, Montreal\, Quebec\, H3G 1M8\, Canada
CATEGORIES:CANSSI Quebec
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/Quebec-Postdoc-Day-2025-General-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250804T123000
DTEND;TZID=America/Chicago:20250804T123000
DTSTAMP:20260511T023622
CREATED:20250718T033125Z
LAST-MODIFIED:20250728T043138Z
UID:28057-1754310600-1754310600@canssi.ca
SUMMARY:Informal Networking Lunch at JSM 2025
DESCRIPTION:Join Us\nIf you are planning to attend the Joint Statistical Meetings (JSM 2025) in Nashville\, Tennessee\, in August\, we invite you to join us for an Informal Networking Lunch co-hosted by CANSSI and the Institute of Mathematical Statistics (IMS). \nThe lunch will take place at Boqueria\, 5005 Broadway Place\, on Monday\, August 4\, from 12:30 to 1:50 p.m. \nConnect with fellow statisticians\, share ideas\, and enjoy great food in a relaxed setting. \nSign Up to Save Your Spot\nWe’ve closed the registration because this event has reached capacity.
URL:https://canssi.ca/events/lunch-jsm-2025/
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-IMS-JSM-2025-Lunch.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250613T100000
DTEND;TZID=America/Vancouver:20250613T110000
DTSTAMP:20260511T023622
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:20260511T023622
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;VALUE=DATE:20250525
DTEND;VALUE=DATE:20250529
DTSTAMP:20260511T023622
CREATED:20250219T184653Z
LAST-MODIFIED:20250313T042051Z
UID:27350-1748131200-1748476799@canssi.ca
SUMMARY:2025 Statistical Society of Canada Annual Meeting
DESCRIPTION:Date: Sunday\, May 25\, to Wednesday\, May 28\, 2025\nTime: All day\nLocation: University of Saskatchewan\, 105 Administration Place\, Saskatoon\, Saskatchewan S7N 5A2 \nCANSSI is proud to be a Platinum Co-sponsor of the 2025 Statistical Society of Canada (SSC) Annual Meeting. \nThe 2025 SSC Annual Meeting will take place at the University of Saskatchewan in Saskatoon\, Saskatchewan\, and will feature a full program that includes workshops\, a student poster competition\, award presentations\, and more. The Canadian Statistics Student Conference 2025 will take place at the same location one day before the Annual Meeting. \nRegistration for the Annual Meeting is now open. \nVISIT THE SSC WEBSITE FOR FULL DETAILS.
URL:https://canssi.ca/events/2025-ssc-annual-meeting/
LOCATION:University of Saskatchewan\, 105 Administration Place\, Saskatoon\, Saskatchewan\, S7N 5A2\, Canada
ATTACH;FMTTYPE=image/jpeg:https://canssi.ca/wp-content/uploads/SaskatoonSSC_2025.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Regina:20250524T080000
DTEND;TZID=America/Regina:20250524T180000
DTSTAMP:20260511T023622
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/Winnipeg:20250512T090000
DTEND;TZID=America/Winnipeg:20250516T153000
DTSTAMP:20260511T023622
CREATED:20250225T030508Z
LAST-MODIFIED:20250423T235008Z
UID:27387-1747040400-1747409400@canssi.ca
SUMMARY:CHI/CANSSI Prairies Workshop: Causal Inference: Insights and Applications
DESCRIPTION:Date: Monday\, Wednesday\, Friday\, May 12\, 14\, and 16\, 2025\nTime: 9:00 a.m.–3:30 p.m.\nPlace: Hybrid (in person and on Zoom); University of Manitoba\, Bannatyne Campus\, Chown Building\, Room 207 A&B \nWe encourage participants within Manitoba to attend in person. \nWorkshop Description\nThis three-day workshop on “Causal Inference: Insights and Applications” is organized by the George & Fay Yee Centre for Healthcare Innovation (CHI) at the University of Manitoba and is the fourth workshop in the CANSSI Prairies Workshop Series in Data Science. It will equip researchers with the essential tools needed to effectively analyze and interpret observational data. Participants will explore foundational concepts\, causal diagrams\, and statistical methods for adjusting confounding variables. Topics will include non-parametric techniques\, propensity score methods\, doubly robust approaches\, and machine learning strategies. \nThe workshop will be presented by Sumeet Kalia (Department of Statistics\, University of Manitoba)\, Brenden Dufault (George & Fay Yee Centre for Healthcare Innovation\, University of Manitoba)\, and Amani Hamad (Department of Community Health Sciences\, University of Manitoba) and features hands-on sessions using R\, real-world case studies\, and interactive discussions to enhance understanding of study design and data analysis. This workshop is ideal for professionals\, academics\, and graduate students in statistics\, data science\, and health sciences who wish to improve their expertise in observational research. \nRefine your research skills and gain confidence in tackling complex observational studies—register today! \nCost\n\nAcademic trainees and students: $100\nStaff of non-profit organizations (including postdocs and early career researchers): $300\nIndustry professionals: $600\n\nIn line with CANSSI Prairies’ commitment to enhancing knowledge and skills in various areas of data science\, we are pleased to announce that support is available to provide a 50% discount on the registration fees for the first 15 students and five postdocs or early career researchers (held their first independent academic position within the past five years) who register.\n \nFor more information\, please contact Olawale Ayilara at olawale.ayilara@umanitoba.ca. \nRegistration\nREGISTER ON EVENTBRITE \nWorkshop Outline\nDay 1: Foundations and Core Concepts\n\nWelcome and Introduction\n\nBrief overview of workshop objectives/topics\nIntroduction of instructors and participants\n\n\nKey Concepts in Observational Studies – Dr. Amani Hamad\n\nRole of observational studies in causal inference\nMain observational study designs and their key features\, strengths and limitations\nCommon biases in observational studies (selection bias\, information bias\, confounding)\n\n\nCounterfactuals and Causal Diagrams – Brenden Dufault\n\nNon-parametric adjustment\nEncoding our causal assumptions with directed acyclic graphs (DAGs)\nHow to understand and diagnose common biases using DAGs (selection bias\, information bias\, confounding)\nSoftware for DAGs\nPractical applications of DAGs for observational studies and imperfect RCTs\n\n\nStatistical Methods for Confounding Adjustment Part I – Brenden Dufault\n\nStratification\nMultivariable regression\nG-computation\nFront door adjustment\n\n\n\nDay 2: Statistical Methods for Addressing Bias – Brenden Dufault\n\nPropensity Scores\n\nTheory of balancing scores for confounder adjustment\nEstimands beyond the average treatment effect\nPropensity score methods: matching\, stratification\, and weighting\nGuided exercises using statistical software (RStudio)\nVisualization and diagnostics\n\n\nSpecialized Methods\n\nParametric G-computation for mediation\nIPTW for handling censoring/dropout\nCausal forests for confounder adjustment\n\n\nGroup Discussion and Q&A\n\nDiscussion on the challenges and limitations of the discussed methods\nQ&A session to address participant questions\n\n\n\nDay 3: Advanced Topics in Observational Studies – Dr. Sumeet Kalia\n\nAdvanced Topics\n\nTreatment-confounder feedback\nParametric and non-parametric G-estimation\nDoubly robust estimation\nTargeted maximum likelihood estimation (TMLE)\nMachine learning methods (regression trees; super learner)\nInstrumental variable with binary and continuous treatments\nSensitivity analysis for unmeasured confounding (negative control exposure and outcome; E-value)\n\n\nCase Studies in Observational Research\n\nAnalysis of real-world observational studies\nGroup discussions on methodology and interpretation\n\n\nConclusion and Next Steps\n\nSummary of the workshop\, highlights\, and key takeaways\n\n\n\nAbout the Speakers\nDr. Sumeet Kalia is an Assistant Professor in the Department of Statistics at the University of Manitoba. He earned his PhD in Biostatistics from the University of Toronto with a dissertation titled Causal Inference Using Electronic Health Records in Primary Care. Dr. Kalia also holds an MSc in Biostatistics from Western University. Previously\, he worked as a Research Analyst (Biostatistician) in the Department of Family and Community Medicine at the University of Toronto\, conducting applied and methodological research on causal inference using primary care electronic health records.\nBrenden Dufault is a Biostatistical Consultant with the George & Fay Yee Centre for Healthcare Innovation\, University of Manitoba\, with over 15 years working in clinical trials\, medicine\, and epidemiology. He specializes in the analysis of observational data using causal methods\, and teaches workshops on statistical programming and applied statistics.\nDr. Amani Hamad is an Assistant Professor in the Department of Community Health Sciences at the University of Manitoba. She is the Canada Research Chair in Population Data Science and Data Curation (Tier II) and is a Research Scientist at the Manitoba Centre for Health Policy (MCHP). Dr. Hamad earned her PhD in Pharmacy from the University of Manitoba and completed a postdoctoral fellowship at the George & Fay Yee Centre for Healthcare Innovation Data Science platform. Her research expertise includes population data science\, pharmacoepidemiology\, maternal and child health\, and mental health.\n\nAbout the Series\nThe CANSSI Prairies Workshop Series in Data Science offers an excellent opportunity for individuals to enhance their knowledge and skills in various areas of data science. Through a series of engaging and interactive hybrid (online and in-person) sessions\, participants have the opportunity to explore new topics\, learn cutting-edge techniques\, and connect with experts in the field.
URL:https://canssi.ca/events/chi-canssi-prairies-workshop-causal-inference/
LOCATION:University of Manitoba (Bannatyne Campus)\, 753 McDermot Avenue\, Winnipeg\, Manitoba\, R3E 0T6\, Canada
CATEGORIES:CANSSI Prairies
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Prairies-Workshop-May-2025-3.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250508T130000
DTEND;TZID=America/Toronto:20250508T140000
DTSTAMP:20260511T023622
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/Toronto:20250505T120000
DTEND;TZID=America/Toronto:20250505T160000
DTSTAMP:20260511T023622
CREATED:20250305T201850Z
LAST-MODIFIED:20250312T152815Z
UID:27475-1746446400-1746460800@canssi.ca
SUMMARY:Florence Nightingale Day 2025 at York University
DESCRIPTION:Date: Monday\, May 5\, 2025\nTime: 12 noon–4 p.m.\nLocation: York University\, Markham campus (1 University Boulevard\, Markham)\, Room 4040 \nFlorence Nightingale Day 2025 at York 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. \nAt York\, Florence Nightingale Day 2025 will be co-hosted on Monday\, May 5 (a professional activity day in York Region high schools)\, by the Canadian Statistical Sciences Institute (CANSSI) and York University’s Department of Mathematics and Statistics. The event will take place at York’s Markham campus and will include fun hands-on activities\, a panel discussion featuring statistics professionals\, and opportunities for participants to ask questions about studying and working in statistics. \nA Special Invitation for High School Students\nIf you are a high school student with an interest in math and numbers\, here’s what you will gain by attending: \n\nAn understanding of the strong benefits of studying statistics for your future career path\nA glimpse of what studying statistics in university is like\n\nThe day is part of a movement to promote diversity in statistics and data science by encouraging and inspiring high school students from all communities to explore statistics. We hope you’ll be able to attend. \nLunch is free for all participating students! \nHow to Participate\nIf you are a high school student and you would like to participate in this event\, please fill out this form and we will contact you: \nGo to the sign-up form. \nIf you have questions about registration or anything else\, please contact us at fnday@yorku.ca. \nHow to Get There\nIf you rely on public transportation\, you can take the Go train to Unionville Station next to York’s Markham campus. \nCheck out the map (select “Markham Campus” from the “Campus Locations” dropdown menu). \nSchedule\n\n\n\nTime\nActivity\n\n\n11:30 a.m.–12:00 noon\nArrival and Check-in\n\n\n12:00 noon–1:00 p.m.\nLunch\, Introductions and Statistics Trivia\n\n\n1:00–2:15 p.m.\nCareer Panel\n\n\n2:15–3:45 p.m.\nInteractive Statistics Activities\n\n\n3:45–4:00 p.m.\nQ&A and Closing Remarks\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/fn-day-2025-at-york/
LOCATION:York University Markham\, 1 University Blvd\, Markham\, Ontario\, L6G 0A1\, Canada
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/FN-Day-at-York.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250502T093000
DTEND;TZID=America/Vancouver:20250502T154500
DTSTAMP:20260511T023622
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Winnipeg:20250425T083000
DTEND;TZID=America/Winnipeg:20250425T170000
DTSTAMP:20260511T023622
CREATED:20250225T045417Z
LAST-MODIFIED:20250407T235700Z
UID:27407-1745569800-1745600400@canssi.ca
SUMMARY:CANSSI Prairies Workshop: Processing and Forecasting with Epidemic Surveillance Data
DESCRIPTION:Date: Friday\, April 25\, 2025\nTime: 8:30 a.m.–5:00 p.m.\nPlace: Hybrid (in person and on Zoom); University of Manitoba\, Fort Garry Campus\, Armes Building\, Room 200 \nWorkshop Description\nThis one-day workshop on “Processing and Forecasting with Epidemic Surveillance Data\,” led by Daniel J. McDonald\, Professor of Statistics at the University of British Columbia\, is the third in the CANSSI Prairies Workshop Series in Data Science. We invite you to join us either in person or online. \nProfessor McDonald outlines his presentation as follows: \n“In this workshop\, I will demonstrate how to use R to load\, process\, inspect\, and forecast aggregate epi surveillance data. I will be presenting a few case studies to motivate the entire pipeline from signal discovery to the production of nowcasts and forecasts. The focus will be on aggregate signals (not line list data)\, such as the counts of new hospitalizations per day per location. I will highlight three software packages our group is developing to aid in these tasks: epidat(r/py) for data acquisition\, epiprocess for signal processing and exploration\, and epipredict for producing forecasts. The sessions will include interactive worksheets and labs for hands-on practice. By the end\, attendees will be equipped to produce forecasts for submission to the Canadian Respiratory ForecastHub.” \nProgram Schedule\n\nData Access\, Versioning\, and Revisions\nNowcasting\nRt Estimation\, Renewal Equations and Compartmental Models\nForecasting and Ensembling\n\nCost and Registration\n\nStudents: $30\nNon-students: $50\n\nREGISTER ON EVENTBRITE \nAbout the Speaker\nDaniel J. McDonald is Associate Professor of Statistics at the University of British Columbia in Vancouver. Before joining UBC\, he spent 8 years on the faculty at Indiana University\, Bloomington. Daniel did his undergraduate studies at Indiana University where he received a Bachelor of Science in Music with a concentration in cello performance from the Jacobs School of Music and a Bachelor of Arts in economics and mathematics. He received his PhD in Statistics in 2012 from Carnegie Mellon University\, and his dissertation was awarded the Umesh Gavasakar Memorial Thesis Award. In 2017\, he was a recipient of the Indiana University Trustees Teaching Award. In 2018\, he received a National Science Foundation CAREER award. \nDaniel’s methodological research involves the estimation and quantification of prediction risk\, especially for complex dependent data. This includes the application of statistical learning techniques to time series prediction problems\, as well as investigations of cross-validation for risk estimation. To promote adoption of these methods\, he prioritizes open-source software development in R and lower-level languages\, with packages available on CRAN\, GitHub\, and Bioconductor. On the applied side\, previous work focussed on applications in economics\, engineering\, neuroscience and atmospheric science. Current work examines methods for understanding and modelling epidemiological data\, especially forecasting\, nowcasting\, and software development with Carnegie Mellon University’s Delphi Research Group. \n\nAbout the Series\nThe CANSSI Prairies Workshop Series in Data Science offers an excellent opportunity for individuals to enhance their knowledge and skills in various areas of data science. Through a series of engaging and interactive hybrid (online and in-person) sessions\, participants have the opportunity to explore new topics\, learn cutting-edge techniques\, and connect with experts in the field.
URL:https://canssi.ca/events/canssi-prairies-mcdonald/
LOCATION:University of Manitoba (Fort Garry Campus)\, 66 Chancellors Circle\, Winnipeg\, Manitoba\, R3T 2N2\, Canada
CATEGORIES:CANSSI Prairies
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Prairies-Workshop-April-2025.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250410T130000
DTEND;TZID=America/Toronto:20250410T140000
DTSTAMP:20260511T023622
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/Halifax:20250404T120000
DTEND;TZID=America/Halifax:20250404T130000
DTSTAMP:20260511T023622
CREATED:20250317T174132Z
LAST-MODIFIED:20250326T191443Z
UID:27560-1743768000-1743771600@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: MURPH: Generating Reproducible Ecological Research Through Accessible Data Management and Communication Practices
DESCRIPTION:Date: Friday\, April 4\, 2025\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: Room 137\, Huggins Science Hall\, Acadia University\, and on Zoom \nJoin Us\nThis talk will be presented by Paige Levangie\, an MSc student in the Department of Biology at Acadia University in Nova Scotia. It’s the sixth and final event in this year’s Atlantic Canada Data Science Tour\, a hybrid seminar series organized by CANSSI Atlantic and geared toward upper-level undergraduates in statistics or computer science programs. The host will be Hugh Chipman\, Professor in the Department of Mathematics and Statistics at Acadia University. \nWe invite you to join us in person or online! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nPresentation Abstract\nThe introduction of research data management policy in Canada and subsequent data management plans attempt to provide more standard approaches to conducting and communicating research data to ensure that it is FAIR: (1) Findable\, (2) Accessible\, (3) Interoperable\, and (4) Reusable. Globally\, the emergence of the FAIR principles promotes the use of open access research tools to help format\, analyze\, and communicate research data. Making research data available is a crucial component to current research data management policy that requires researchers to upload research data to online repositories like OBIS\, GBIF\, and Dataverse. These repositories each have differing data standards (e.g.\, the Darwin Core Archive) that can be confusing to understand and use. In addition to data formats and storage\, coding languages like R and accompanying interface software RStudio are popular and used to analyze and visualize data within many disciplines including ecology\, yet require training and expertise. The increasing popularity of Large Language Models like ChatGPT and CoPilot to help create code to solve complex problems complicates the ability to provide detailed and accurate user prompts and contributes to researchers being undertrained and/or overconfident in their research data management abilities. \nCurrent infrastructure for research data management tools is not equipped to address the growing variety in data formats and types within different ecological fields. Researchers are not equipped or trained with the proper skills and attempt to meet research data management policy requirements after the fact. This causes most ecological research to lack reproducibility and limits accessibility. To combat a lack of understanding in data formatting and coding skills\, an open access free interactive tool\, MURPH\, was created to allow researchers to upload research data and produce various outputs. These outputs will allow users to reformat research data into OBIS format (using Darwin Core standards)\, and produce plots\, tables\, and maps. Users receive outputs and code used to generate them outside of the tool\, which serves as a guide for future work. Overall\, this tool is aimed to increase the knowledge\, education\, and understanding of research data management and communication practices in ecological research as they are made to be accessible\, interactive\, reproducible\, and presented in formats that are broadly understood by online repositories. \nAbout the Presenter\nPaige Levangie is from West Hants\, Nova Scotia\, and has attended Acadia University since 2021. She completed her Bachelor of Science Honours at Queen’s University and moved back home to start her master’s immediately after graduation. She is passionate about open research\, data management\, and coding in R. Outside of school\, Paige spends most of her time curling\, hanging out with her dogs\, or cheering on her husband’s tug-of-war team.
URL:https://canssi.ca/events/atlantic-tour-murph/
LOCATION:Acadia University\, 15 University Avenue\, Wolfville\, Nova Scotia\, B4P 2R6\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Atlantic-Tour-Apr-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250404T103000
DTEND;TZID=America/Vancouver:20250404T120000
DTSTAMP:20260511T023622
CREATED:20250312T043357Z
LAST-MODIFIED:20250317T185206Z
UID:27501-1743762600-1743768000@canssi.ca
SUMMARY:CANSSI SSC and 2025 Van Eeden Seminar: From Diffusion Models to Schrödinger Bridges—When Generative Modeling Meets Optimal Transport
DESCRIPTION:Date: Friday\, April 4\, 2025\nTime: 10:30–12:00 Pacific time\nLocation: Online or in person at the Earth Sciences Building (ESB) 5104\, 2207 Main Mall\, University of British Columbia\, Vancouver\, B.C. \nJoin Us\nThis special event represents a convergence of the CANSSI SSC Seminar on Innovations in Statistics and Data Science and the Constance van Eeden Seminar\, an annual event held at the University of British Columbia. \nThe CANSSI SSC Seminar is a new series co-sponsored by CANSSI and the Statistical Society of Canada (SSC) that brings distinguished researchers in statistical sciences to CANSSI member universities across Canada. The series promotes interactions between leading researchers and statistical sciences faculty members and students\, particularly at smaller institutions. \nThe Constance van Eeden seminar is a yearly event in which graduate students from the University of British Columbia (UBC)’s Department of Statistics vote for their favourite statisticians. The winner is contacted by the organizing committee and invited to give a talk in the department’s seminar. The speaker spends one or two days on campus\, and graduate students have the opportunity to have lunch and dinner with them. \nRegistration\nTo register for online or in-person participation\, visit the event web page. \nAbout This Year’s Speaker\nThis year’s speaker is Dr. Arnaud Doucet\, Professor of Statistics at the University of Oxford and Senior Staff Research Scientist at Google DeepMind. Dr. Doucet’s research interests lie in the development and analysis of efficient computational methods for inference and learning\, machine learning\, signal processing\, and related areas. \nHis talk is titled “From Diffusion Models to Schrödinger Bridges—When Generative Modeling Meets Optimal Transport.” \n  \nPresentation Abstract\nDenoising diffusion models have revolutionized generative modeling. Conceptually\, these methods define a transport mechanism from a noise distribution to a data distribution. Recent advancements have extended this framework to define transport maps between arbitrary distributions\, significantly expanding the potential for unpaired data translation. However\, existing methods often fail to approximate optimal transport maps\, which are theoretically known to possess advantageous properties. In this talk\, we will show how one can modify current methodologies to compute Schrödinger bridges—an entropy-regularized variant of dynamic optimal transport. We will demonstrate this methodology on a variety of unpaired data translation tasks.
URL:https://canssi.ca/events/canssi-ssc-2025-van-eeden-seminar/
LOCATION:University of British Columbia\, Earth Sciences Building (ESB) 5104\, Vancouver\, British Columbia\, V6T 1Z4\, Canada
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-SSC-Van-Eeden-2025-v1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20250320T130000
DTEND;TZID=America/Toronto:20250320T140000
DTSTAMP:20260511T023622
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/Toronto:20250314T103000
DTEND;TZID=America/Toronto:20250314T143000
DTSTAMP:20260511T023622
CREATED:20241216T215802Z
LAST-MODIFIED:20250312T184155Z
UID:26868-1741948200-1741962600@canssi.ca
SUMMARY:CANSSI Quebec 2025 Stats in a Flash Competition
DESCRIPTION:Event date: Friday\, March 14\, 2025\nEntry deadline: Friday\, March 7\, 2025\nTime: 10:30 a.m.–2:30 p.m. ET\nLocation: Hall Building\, Room H-1220\, Concordia University\, Montreal\, Quebec\, and on Zoom \nCould you present your statistics research in three minutes? \nThat’s the challenge facing participants in CANSSI Quebec’s second annual Stats in a Flash: 180-Second Thesis Competition. \nThis year’s event has a twist: In addition to the regular competition for master’s and PhD students\, there will be a new non-competitive section for Quebec faculty members willing to take up the challenge of presenting their statistics research while taking the opportunity to discuss potential openings in their research groups. \nInterested in participating? See the instructions below. \nInterested in watching in person or online? Register as an attendee on Eventbrite. \nUse this Zoom link to watch the event. \nHow It Works\nGraduate Students\nThe Stats in a Flash competition is designed to promote academic excellence as well as to foster effective communication and presentation skills. It provides a unique platform for participants to showcase their research and enhance their communication abilities within the statistical sciences community. \n\nThe student competition is open to full-time master’s and PhD students in thesis-based statistical sciences programs at Quebec universities.\nParticipants deliver a three-minute presentation based on their primary research with the help of a single PowerPoint slide. The presentations may be done in either French or English.\nAll presentations must be delivered in person\, and all participants agree to be photographed and digitally recorded and to allow any recordings to be made public.\nA panel of judges evaluates the presentations based on communication\, comprehension\, and engagement.\n\nPrizes of $500\, $250\, and $125 will be awarded for the top presentations\, and there will also be a special Audience Choice Prize of $125. \nFor the full rules and regulations\, read this PDF document. \nTo enter the Stats in a Flash competition\, register as a student presenter on Eventbrite. \nFaculty Members\nFor 2025\, the event will include a separate non-competitive session in which faculty members from Quebec universities are invited to use the same format—a three-minute talk with one PowerPoint slide—to present their statistical sciences research. Faculty participants will also be given time (over and above the three minutes!) to discuss potential openings in their research groups. \nTo participate as a faculty member\, register as a faculty presenter on Eventbrite. \nSchedule\n10:30–11:30 a.m. | Faculty presentations \n11:30 a.m.–12:30 p.m. | Complimentary lunch for participants and attendees \n12:30–2:00 p.m. | Student presentations \n2:15 p.m. | Distribution of prizes
URL:https://canssi.ca/events/canssi-quebec-2025-stats-in-a-flash-competition/
LOCATION:Concordia University\, 1400 De Maisonneuve Boulevard W\, Montreal\, Quebec\, H3G 1M8\, Canada
CATEGORIES:CANSSI Quebec
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Quebec-Stats-Flash-2025-EN-2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250308T100000
DTEND;TZID=America/Vancouver:20250308T153500
DTSTAMP:20260511T023622
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
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20250307T120000
DTEND;TZID=America/Halifax:20250307T130000
DTSTAMP:20260511T023622
CREATED:20250214T064450Z
LAST-MODIFIED:20250220T232902Z
UID:27297-1741348800-1741352400@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: Mediation Analysis of Recurrent Events
DESCRIPTION:Date: Friday\, March 7\, 2025\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: On Zoom\, live from Memorial University of Newfoundland \nThis talk will be presented by Shenita Pramij\, a PhD student in the Department of Mathematics and Statistics at Memorial University of Newfoundland. It’s the fifth event in the Atlantic Canada Data Science Tour\, a hybrid seminar series organized by CANSSI Atlantic and geared toward upper-level undergraduates in statistics or computer science programs. The host will be Yildiz Yilmaz\, Associate Professor of Statistics in the Department of Mathematics and Statistics at Memorial University. \nThis event will be online only\, live from Memorial University of Newfoundland. We invite you to join us! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nPlease note that this talk will begin at noon Atlantic time (not Newfoundland time). \nAbout the Presentation\nInferring the direct effects of exposure in recurrent event processes\, while accounting for mediating factors\, is crucial\, yet conventional approaches face significant limitations in the presence of complex causal relationships. We introduce two methods to address these challenges. We first explore a two-stage sequential G-estimation method to estimate the controlled direct effect of a randomly assigned exposure\, while accounting for potential mediators and confounders\, using intensity-based models of recurrent event processes. We also introduce a novel one-stage estimation method based on the estimating equations framework\, leveraging the sequential G-estimation principle. We demonstrate that both methods yield unbiased controlled direct effect estimates. The one-stage method also enables the analytical derivation of an estimator for the standard error of the direct effect estimator. We illustrate our approach using a hospital readmission dataset of colorectal cancer patients to estimate the controlled direct effect of sex differences on hospital readmission. \nAbout the Presenter\n\nShenita Pramij is a PhD student in Statistics at Memorial University of Newfoundland. Her research focuses on mediation analysis\, with a particular emphasis on estimating controlled direct effects in recurrent event processes. She has broad interests in modelling complex processes with applications in healthcare and public policy\, particularly in using statistical methods to analyze disease dynamics and assess intervention effects. \nBeyond her doctoral research\, Shenita has extensive experience in the public sector as a compliance researcher\, where she applies causal inference techniques to evaluate the impact of policies and interventions on compliance. Her work aims to enhance decision-making in public policy and inform targeted interventions. \nShenita holds a Master of Science in Statistics and a Bachelor of Science in Pure Mathematics from Memorial University.
URL:https://canssi.ca/events/atlantic-tour-mediation-analysis/
LOCATION:Memorial University\, St John's\, Newfoundland and Labrador\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Atlantic-Tour-Mar-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20250214T120000
DTEND;TZID=America/Vancouver:20250214T133000
DTSTAMP:20260511T023622
CREATED:20241025T172354Z
LAST-MODIFIED:20241028T234138Z
UID:26608-1739534400-1739539800@canssi.ca
SUMMARY:Get Comfortable Being Uncomfortable: Engaging in Dialogue About Favoritism and Fairness
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\, a leading provider of leadership\, personal development\, and skills-based training opportunities to faculty and staff in higher education. \nWe invite you to join us for this 1.5-hour online workshop led by Sandra Miles\, Head of Practice for Team Development at Academic Impressions. \nThis session can be used to fulfill the CANSSI EDI requirement for CANSSI-supported researchers. \nRegistration\nREGISTER FOR THIS WORKSHOP \nWorkshop Description\nDuring this virtual workshop\, we will explore the ways in which feelings of defensiveness and discomfort can be very common when engaging in conversations around favoritism and unfairness. Even those who have done extensive reading on topics related to conflict management can find themselves fumbling if they haven’t yet reflected on how their personal feelings may impact the ways they show up in the world—and in these difficult conversations. To get more comfortable engaging in these dialogues\, we must first lean into the discomfort of individual reflection and actions that prepare us to enter into them in an open and effective way. You will be given a workbook of activities\, tools\, and resources to help you move beyond simply understanding these key concepts. Throughout the workshop\, you will begin the hard work of interpreting how favoritism can show up in every aspect of the work we do\, and how an orientation around fairness improves relationships\, morale\, and trust. \nLearning Outcome\nAfter participating\, you will leave with tools to identify a propensity towards favoritism and become more intentional in your interactions with colleagues and students. \nWho Should Attend\nFaculty who are ready to move beyond a baseline readiness to effectively engage in difficult conversations. You will be equipped with tools and best practices to help you feel more comfortable participating in these dialogues in the future. \n\nWorkshop Leader\nSandra Miles\, PhD\nHead of Practice for Team Development\, 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. In 2024\, she transitioned to specialize in the team development space supporting the growth of trust and effectiveness of high-performing teams among leaders in higher education. \nSandra completed her doctoral work at Florida State University in 2012\, earning a PhD 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/get-comfortable/
CATEGORIES:EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/EDI-Get-Comfortable-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20250131T120000
DTEND;TZID=America/Halifax:20250131T130000
DTSTAMP:20260511T023622
CREATED:20241231T063158Z
LAST-MODIFIED:20250116T175413Z
UID:26936-1738324800-1738328400@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: Your Data Are a Fingerprint: Why Anonymization is Not Anonymous and How Statistics Can Protect You
DESCRIPTION:Date: Friday\, January 31\, 2025\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: On Zoom\, live from the University of New Brunswick (Saint John) \nThis talk will be presented by Dylan Spicker\, an Assistant Professor in the Department of Mathematics and Statistics at the University of New Brunswick (Saint John). It’s the fourth event in the Atlantic Canada Data Science Tour\, a hybrid seminar series organized by CANSSI Atlantic and geared toward upper-level undergraduates in statistics or computer science programs. The host will be Joanna Mills Flemming\, Professor in the Department of Mathematics and Statistics and Associate Dean of Graduate and Global Relations at Dalhousie University. Joanna is also the Regional Director of CANSSI Atlantic. \nThis event will be online only\, live from the University of New Brunswick. We invite you to join us! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nAbout the Presentation\nThe collection and analysis of data have become ubiquitous across nearly every domain (including healthcare\, social media\, and government). Much of the information that is collected\, stored\, and analyzed is private or sensitive\, and as such\, there is increasing pressure to ensure that individual privacy is maintained. Failure to do so can have serious consequences for the individuals involved. Unfortunately\, privacy researchers have demonstrated that every statistical analysis can inadvertently leak private information unless the analysis is designed to meet rigorous standards of privacy. This is true even when the data have been “anonymized” by removing personal identifiers (such as names\, addresses\, or social insurance numbers). In this talk\, we will explore these privacy pitfalls and outline the work that researchers are doing to overcome them. \nAbout the Presenter\n\nDylan Spicker (they/them) is an Assistant Professor at the University of New Brunswick (Saint John). \nThey completed their PhD at the University of Waterloo in the summer of 2022 and their postdoc at McGill University in 2023. \nDylan’s research focuses on areas of causal inference\, and specifically methodologies related to dynamic treatment regimes. During their graduate studies\, their research focused on measurement error and causal inference. Briefly\, measurement error occurs whenever we are interested in measuring something and we do a bad job of it. This happens in almost every study that is run\, and unfortunately means that the conclusions that we draw may not be accurate; statistical work on measurement error tries to correct this. Causal inference asks questions of the form “Does X cause Y?” (For instance\, “Does smoking cause lung cancer?” (Yes\, it does.)) They have a keen interest in providing a theoretical basis for (comparatively) straightforward methods\, which are easy to use for non-statisticians\, while exhibiting provably good theoretical properties. \nDuring their postdoc\, Dylan explored problems related to privacy and dynamic treatment regimes\, where they sought to determine ways that an individual’s personal health data can be protected\, while gleaning the useful insights that we seek. \nOutside of causal inference and measurement error\, Dylan is interested in machine learning\, and in particular in trying to establish a statistical basis for novel machine learning techniques (including questions related to inference\, interpretability\, and model selection). \nDylan previously did an undergraduate degree in Finance and Mathematics at Queen’s University (they transferred there after completing their first year at the University of Waterloo/Wilfrid Laurier University in the “Double Degree” program)\, and a Master of Statistics at Waterloo. \nOutside of their research\, they pay very close attention to sports\, mostly hockey (and how statistics is\, or should be\, applied there)\, play music (without any connection to statistics)\, and enjoy board/video games (with varying degrees of statistical relevance). They have a cat (Charles) who is wonderful.
URL:https://canssi.ca/events/atlantic-tour-data-fingerprint/
LOCATION:University of New Brunswick Saint John\, 100 Tucker Park Rd\, Saint John\, New Brunswick\, E2K 5E2\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/atlantic-tour-jan31.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20241129T120000
DTEND;TZID=America/Halifax:20241129T130000
DTSTAMP:20260511T023622
CREATED:20241104T180056Z
LAST-MODIFIED:20241105T235407Z
UID:26624-1732881600-1732885200@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: Using Machine Learning to Forecast Changes in Canada’s Food Prices: Canada’s Food Price Report 2025
DESCRIPTION:Date: Friday\, November 29\, 2024\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: 550 University Ave\, Charlottetown\, Prince Edward Island\, Canada C1A 4P3 \nThis talk will be presented by Kristina Kupferschmidt\, an Assistant Professor in the School of Mathematical and Computational Sciences at the University of Prince Edward Island. It’s the third event in the Atlantic Canada Data Science Tour\, a hybrid seminar series organized by CANSSI Atlantic and geared toward upper-level undergraduates in statistics or computer science programs. The host will be Joanna Mills Flemming\, Professor in the Department of Mathematics and Statistics and Associate Dean of Graduate and Global Relations at Dalhousie University. Joanna is also the Regional Director of CANSSI Atlantic. \nWe invite you to join us in person or online! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nAbout the Presentation\nUnderstanding how food prices change is essential for Canadian households\, especially with recent inflation and global challenges impacting affordability. Each year\, Canada’s Food Price Report (CFPR) predicts food price trends for the coming year. While recent reports have used machine learning (ML) to improve these forecasts\, the 2024 and 2025 editions have also incorporated a “human-in-the-loop” approach to model development. In this study\, we explored new strategies for working with food pricing experts to further improve forecast reliability. We investigated how different types of models predict changes in food prices and examined how sensitive these models are to various sets of data. \nAbout the Presenter\nKristina Kupferschmidt is a newly appointed Assistant Professor in the School of Mathematical and Computational Sciences at the University of Prince Edward Island. She recently completed a PhD in computer engineering with a focus on machine learning at the University of Guelph. \nKristina’s research focuses on applied artificial intelligence (AI). Her interests lie in responsible AI deployment and improving the real-world translation of machine learning (ML) technologies. She has co-founded two companies\, worked as a biomedical engineer and ML developer in both small startup and industry environments\, and is currently the Lead Scientist-in-Residence for the NEXT-AI accelerator program. In addition to her work\, Kristina serves as the co-chair of the CEPS Indigenization\, Equity\, Diversity\, and Inclusion Committee and is actively conducting research on inclusivity within the field of AI.
URL:https://canssi.ca/events/atlantic-tour-using-machine-learning/
LOCATION:University of Prince Edward Island\, 550 University Avenue\, Charlottetown\, Prince Edward Island\, C1A 4P3\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Atlantic-Tour-Nov-29-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20241128T153000
DTEND;TZID=America/Toronto:20241128T163000
DTSTAMP:20260511T023622
CREATED:20241116T165850Z
LAST-MODIFIED:20241208T030130Z
UID:26676-1732807800-1732811400@canssi.ca
SUMMARY:CANSSI SSC Seminar: Predictive Modeling and Balance Property through Autocalibration
DESCRIPTION:Date: Thursday\, November 28\, 2024\nTime: 3:30–4:30 p.m. ET\nLocation: Université du Québec à Montréal\, Pavillon Président Kennedy\, 201\, Av. Président Kennedy\, PK-5115\, Montréal (Métro Place des Arts) and online \nThis hybrid talk by Julien Trufin (Université Libre de Bruxelles\, Belgium) is part of the CANSSI SSC Seminar on Innovations in Statistics and Data Science\, a new series co-sponsored by CANSSI and the Statistical Society of Canada that brings distinguished researchers in statistical sciences to CANSSI member universities across Canada. The series promotes interactions between leading researchers and statistical sciences faculty members and students\, particularly at smaller institutions. \nThis event is hosted by the Centre de recherche facultaire en statistique et science des données (STATQAM) at Université du Québec à Montréal. \nWe invite you to join the presentation in person or online. \nThis event is past. \nWATCH THE RECORDING\n(password: z^E=#K@5) \nAbout the Presentation\nMachine learning techniques provide actuaries with predictors exhibiting high correlation with claim frequencies and severities. However\, these predictors generally fail to achieve financial equilibrium and thus do not qualify as pure premiums. Autocalibration effectively addresses this issue since it ensures that every group of policyholders paying the same premium is on average self-financing. This talk proposes to look at recent results concerning autocalibration. In particular\, we present a new characterization of autocalibration which enables us to identify whether a predictor is autocalibrated or not\, we study a method (called balance correction) for obtaining an autocalibrated predictor from any regression model\, we highlight the effect of balance correction on resulting pure premiums\, and finally we go through some performance criteria that are particularly relevant for autocalibrated predictors. \nAbout the Presenter\nJulien Trufin has been a Professor of Actuarial Science in the Department of Mathematics at the Université Libre de Bruxelles (ULB) since 2023. He was an Associate Professor between 2014 and 2023 in the same department. Previously\, he was an Assistant Professor between 2012 and 2014 at Université Laval in Quebec\, Canada. His main research fields are: \n\nRisk classification: insurance pricing and machine learning techniques\nLoss reserving: collective and individual methods\nCredibility theory\nStochastic inequalities: stochastic orders and dependence concepts\nRisk measures\nRuin theory\n\nHe is an editor for two international journals: \n\nCo-Editor of the European Actuarial Journal (2021–present);\nAssociate Editor of ASTIN Bulletin: The Journal of the International Actuarial Association (2018–present).\n\nHe also served as Associate Editor of Methodology and Computing in Applied Probability from 2015 to 2024.
URL:https://canssi.ca/events/canssi-ssc-seminar-uqam/
LOCATION:UQAM\, Pavillon Président Kennedy\, 201\, Av. Président Kennedy\, PK-5115\, Montréal\, Québec\, H2X 3Y7\, Canada
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-SSC-Seminar-Nov-28-3.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20241122T120000
DTEND;TZID=America/Vancouver:20241122T133000
DTSTAMP:20260511T023622
CREATED:20241021T022809Z
LAST-MODIFIED:20241024T011154Z
UID:26578-1732276800-1732282200@canssi.ca
SUMMARY:Intersectionality in Higher Education
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\, a leading provider of leadership\, personal development\, and skills-based training opportunities to faculty and staff in higher education. \nWe invite you to join us for this 1.5-hour online workshop led by Sandra Miles\, Head of Practice for Team Development at Academic Impressions. \nThis session can be used to fulfill the CANSSI EDI requirement for CANSSI-supported researchers. \nRegistration\nREGISTER FOR THIS WORKSHOP \nWorkshop Description\nHighly inclusive leaders strive to respect and value people from diverse backgrounds based on categories like gender\, race\, class\, sexual orientation\, religion\, ability\, etc. This session will focus on intersectionality—on the ways that individuals can face multiple forms of oppression due to their membership in more than one non-dominant social identity. We will explore how leaders can cultivate inclusion by addressing the complex\, cumulative effects of intersectionality. \nThis interactive presentation empowers participants to explore\, confront\, and recalibrate any personal desire or understandings that may cause us to put our colleagues in boxes based on one identity\, rather than seeing them as the sum total of all of their identities. \nLearning Outcome\nAfter participating\, you will leave with tools to help continuously uncover and deepen your understanding of personal biases and acquire skills to compassionately help others recognize their own biases. \nWho Should Attend\nFaculty who are interested in learning about intersectionality within a higher education setting. This course is most beneficial to anyone unfamiliar with intersectionality or interested in exploring effective intervention techniques to use with colleagues\, administrative leaders\, and students. \n\nWorkshop Leader\nSandra Miles\, PhD\nHead of Practice for Team Development\, 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. In 2024\, she transitioned to specialize in the team development space supporting the growth of trust and effectiveness of high-performing teams among leaders in higher education. \nSandra completed her doctoral work at Florida State University in 2012\, earning a PhD 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/intersectionality/
CATEGORIES:EDI
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/EDI-Intersectionality-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20241115T074500
DTEND;TZID=America/Vancouver:20241115T153000
DTSTAMP:20260511T023622
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/Halifax:20241025T120000
DTEND;TZID=America/Halifax:20241025T130000
DTSTAMP:20260511T023622
CREATED:20241009T011118Z
LAST-MODIFIED:20241015T220915Z
UID:26279-1729857600-1729861200@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: Incorporating Data-driven Models towards Actuarial Problems
DESCRIPTION:Date: Friday\, October 25\, 2024\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: MULH2032 (Mulroney Hall)\, 4130 University Avenue\, Antigonish\, Nova Scotia\, Canada B2G 2W5 \nActuarial science is a discipline which draws on the mathematics of probability and statistics to assess financial risks in the field of insurance. With the growing availability of data\, actuaries are continuously updating their modelling frameworks to improve the way they assess risk. This seminar will introduce some of the data-driven approaches that can be used to address real-world actuarial problems and demonstrate how traditional methods can be updated to better prepare actuaries to make informed decisions while modelling future trends. \nThe talk will be presented by Kyran Cupido\, an Assistant Professor in the Department of Mathematics and Statistics at St. Francis Xavier University. It’s the second event in the Atlantic Canada Data Science Tour\, a hybrid seminar series geared toward upper-level undergraduates in statistics or computer science programs. The host will be Joanna Mills Flemming\, Professor in the Department of Mathematics and Statistics and Associate Dean of Graduate and Global Relations at Dalhousie University. Joanna is also the Regional Director of CANSSI Atlantic. \nWe invite you to join us in person or online! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nAbout the Presenter\nKyran Cupido is an Assistant Professor in the Department of Mathematics and Statistics at St. Francis Xavier University in Antigonish\, Nova Scotia. He completed a PhD in Statistics at Arizona State University\, where he specialized in actuarial science. His research interests include geospatial analysis\, spatial regression modelling\, and data science\, with a particular focus on the actuarial domains of longevity risk and property and casualty (P&C) insurance.
URL:https://canssi.ca/events/atlantic-tour-data-driven-models/
LOCATION:St. Francis Xavier University\, 4130 University Avenue\, Antigonish\, Nova Scotia\, B2G 2W5\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/Atlantic-Tour-Oct-25-EN-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20240927T120000
DTEND;TZID=America/Halifax:20240927T130000
DTSTAMP:20260511T023622
CREATED:20240919T161147Z
LAST-MODIFIED:20240923T160705Z
UID:26191-1727438400-1727442000@canssi.ca
SUMMARY:Atlantic Canada Data Science Tour: What I’m Doing As a Grad Student
DESCRIPTION:Date: Friday\, September 27\, 2024\nTime: 12:00–1:00 p.m. Atlantic time\nLocation: Chase Building Room 319 (3rd Floor)\, 6297 Catine Way\, Department of Mathematics and Statistics\, Dalhousie University\, Halifax \nWhat is it like to do research as a grad student? In the kick-off to CANSSI Atlantic’s Atlantic Canada Data Science Tour\, three master’s students and one PhD student in statistics at Dalhousie University will talk about the path that led them to graduate studies in statistics and the research they are doing. The host will be Joanna Mills Flemming\, Professor in the Department of Mathematics and Statistics and Associate Dean of Graduate and Global Relations at Dalhousie University. Joanna is also the Regional Director of CANSSI Atlantic. \nWe invite you to join us in person or online! (We’ll send you the Zoom link when you register.) \nREGISTER ON EVENTBRITE \nPresenters\n\n  \n“Spatiotemporal Modelling of Lobster Abundance”\nJoseph Barss\, MSc student in statistics\, co-supervised by Professors Joanna Mills Flemming and Theo Michelot \n“Statistics and Fish: How Our Expertise Can Benefit Ecology and Fisheries Science”\nRaphaël McDonald\, PhD student in statistics\, co-supervised by Professor Joanna Mills Flemming and David Keith (Fisheries and Oceans Canada) \n“Event-based Validation Metrics for Hydrodynamic Models”\nEthan O’Connell\, MSc student in statistics\, supervised by Professor Michael Dowd \nFatma Sarhan\, MSc student in statistics\, supervised by Professor Orla Murphy
URL:https://canssi.ca/events/atlantic-tour-grad-students/
LOCATION:Dalhousie University\, Chase Building Room 319 (3rd Floor)\, 6297 Catine Way\, Halifax\, Nova Scotia\, B3H 4R2\, Canada
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/CANSSI-Atlantic-Tour-EN.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20240910T100000
DTEND;TZID=America/Toronto:20240910T170000
DTSTAMP:20260511T023622
CREATED:20240619T182356Z
LAST-MODIFIED:20240819T213822Z
UID:25722-1725962400-1725987600@canssi.ca
SUMMARY:CANSSI Quebec’s Postdoc Day 2024
DESCRIPTION:Join Us\nOn September 10\, CANSSI Quebec will host Postdoc Day 2024 at Concordia University. It’s a chance for the entire statistical sciences community to get to know Quebec-based postdoctoral fellows doing statistics-centred research. The event will feature research presentations by postdocs from across the province and will conclude with a reception. \nWe hope you’ll be able to join us. \nSee a blog post about last year’s Postdoc Day (includes presentation abstracts and YouTube recording). \nEvent Details and Registration\nDate: Tuesday\, September 10\, 2024\nLocation: Concordia University\, 1400 De Maisonneuve W\, Montreal\, LB 921.04 (J.W. McConnell Building) \nREGISTER ON EVENTBRITE \nSchedule\nThe event will take place in the Conference Room of the Department of Mathematics and Statistics of Concordia University (LB 921.04). \n9:45 a.m. | Welcoming Remarks \n10:00 a.m. | Presentation 1 | Rishikesh Yadav (HEC Montréal and McGill University) | Sparse Spatiotemporal Dynamic Generalized Linear Models for Inference and Prediction of Bike Counts \n10:45 a.m. | Presentation 2 | Lara Malayeff (McGill University) | An Adaptive Enrichment Design Using Bayesian Model Averaging for Selection and Threshold-identification of Tailoring Variables \n11:30 a.m. | Presentation 3 | Sébastien Jessup (Concordia University) | Flexible Extreme Thresholds Through Generalised Bayesian Model Averaging \n12:15 p.m. | Lunch Break \n1:15 p.m. | Presentation 4 | Arthur Chatton (Université de Montréal) | What If We Had Built a Prediction Model with a Survival Super Learner Instead of a Cox Model 10 Years Ago? \n2:00 p.m. | Presentation 5 | Chi-Kuang Yeh (University of Waterloo and McGill University) | Positive and Unlabeled Data: Model\, Estimation\, Inference\, and Classification \n2:45 p.m. | Presentation 6 | Dante Mata (Université du Québec à Montréal) | Title to come \n3:30 p.m. | Presentation 7 | Marie Michaelides (Concordia University) | Bayesian Time Varying Conditional Copula Models for Spatio-Temporal Dependence in Crop Yield Data \n4:15 p.m. | Reception
URL:https://canssi.ca/events/canssi-quebecs-postdoc-day-2024/
LOCATION:Concordia University\, 1400 De Maisonneuve Boulevard W\, Montreal\, Quebec\, H3G 1M8\, Canada
CATEGORIES:CANSSI Quebec
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20240708T083000
DTEND;TZID=America/Vancouver:20240710T130000
DTSTAMP:20260511T023622
CREATED:20240319T010916Z
LAST-MODIFIED:20240614T162441Z
UID:25123-1720427400-1720616400@canssi.ca
SUMMARY:CANSSI-CRT Workshop on Modern Methods in Survey Sampling
DESCRIPTION:About This Event\n\n\n\n\n\n\nComplex surveys play an important role in providing information for policy makers and the general public as well as many scientific areas\, such as public health and social science research. The objective of this workshop is to take stock of new developments in the field of survey data\, to bring together some of the most active researchers in the field\, and to identify the current challenges. The workshop is the final activity of a three-year Collaborative Research Team project funded by the Canadian Statistical Sciences Institute. The project is titled Modern Methods in Survey Sampling. The workshop will cover a range of topics\, including \n\nMachine learning methods\nData integration techniques\nHigh-dimensional data\nSmall area estimation\n\nFor more information\, please contact David Haziza at dhaziza@uottawa.ca. \n\n\n\n\nRegistration\nThis three-day event will take place at the University of Ottawa in Ottawa\, Ontario\, Canada. Registration for the event is C$250 and includes the cost of all lunches and coffee breaks. \nA limited number of no-cost guest passes are available for graduate students with limited funding. Please contact David Haziza at dhaziza@uottawa.ca for details. \nREGISTER ON EVENTBRITE \n\n\n\n\nLocation\nSITE Building (STEH0104)\nUniversity of Ottawa\n800 King Edward Avenue\nOttawa\, Ontario \n\n\n\n\nAccommodations\nResidence rooms for graduate students: The organizers have arranged free accommodation for graduate students in the University of Ottawa’s Rideau Residence at 290 Rideau Street. \nThe residence rooms have two double beds and can accommodate up to four people. They come with a private bathroom\, a mini-fridge and microwave\, and air conditioning. \nIf you would like to reserve a residence room\, please contact David Haziza at dhaziza@uottawa.ca. \nHotel accommodations: We have reserved a block of rooms at the Novotel Ottawa City Centre (Novotel Ottawa) at a reduced rate. The reduced rate is 175 Canadian dollars per night + taxes.  \nYou can make a reservation using three different modes (see below). What’s important is that\, regardless of the mode you choose\, you need to use the following code to get the reduced price: 1265702 \nOption 1: You can reserve a room by email. Please write to novotelottawa@novotelottawa.com and mention the code. \nOption 2: You can reserve by phone at 001-613-230-3033\, but don’t forget to mention the code. \nOption 3: You can use the following link  https://book.passkey.com/e/50793164. When making the reservation using this link\, please select “attendee” to continue. \nProgram\nMonday\, July 8\, 2024\n8:15 – 8:45 Registration \n8:45 – 9:00 Introductory remarks \nChair: David Haziza \n9:00 – 9:40 Fitting Classification Trees to Complex Survey Data | Jean Opsomer\, WESTAT \n9:40 – 10:20 Bayesian Tree Models for Data from a Complex Design | Daniell Toth\, U.S. Bureau of Labor Statistics) \n10:20 – 10:50 Coffee break | Session in honour of J.N.K. Rao \n10:50 – 11:20 Permutation Tests Under a Rotating Sampling Plan With Clustered Data | Jiahua Chen\, University of British Columbia \n11:20 – 11:50 Optimal Predictors of General Small Area Parameters Under an Informative Sample Design | Isabel Molina\, Universidad Complutense Madrid \n11:50 – 12:20 Bayesian Empirical Likelihood Methods for Complex Survey Data | Changbao Wu\, University of Waterloo \n12:30 – 14:00 Lunch \nChair: Changbao Wu \n14:00 – 14:40 Random Forests and Mixed Effects Random Forests for Small Area Estimation of General Parameters | Nikos Tzavidis\, University of Southampton \n14:40 – 15:10 Use of Random Forests in Small Area Estimation | Kevin Bosa\, Statistics Canada \n15:10 – 15:40 Coffee break \n15:40 – 16:20 Debiased Calibration Estimation Using Generalized Entropy in Survey Sampling | Jae-Kwang Kim\, Iowa State University \n16:20 – 17:00 Variance Estimation for Survey Estimators Based on Statistical Learning Models| Mehdi Dagdoug\, McGill University \n17:00 – 17:30 Small Area Estimation with Random Forests and the LASSO | Victoire Michal\, McGill University \nTuesday\, July 9\, 2024\nChair: Changbao Wu \n9:10 – 9:50 Weight Smoothing via Design Modeling in Complex Surveys | F. Jay Breidt\, NORC at the University of Chicago \n9:50 – 10:30 Optimal Transport Methods in Survey Sampling | Yves Tillé\, Université de Neuchâtel \n10:30 – 11:00 Coffee break \n11:00 – 11:40 Combining Probability and Non-probability Samples Using Semi-parametric Quantile Regression and a Non-parametric Estimator of the Participation Probability | Emily Berg\, Iowa State University \n11:40 – 12:20 Some New Developments on Likelihood Approaches to Estimation of Participation Probabilities for Non-probability Samples | Jean-François Beaumont\, Statistics Canada \n12:30 – 14:00 Lunch \nChair: David Haziza \n14:00 – 14:40 Statistical Methods for Sampling Cross-classified Populations Under Constraints | Louis-Paul Rivest\, Université Laval \n14:40 – 15:10 Logistic Regression on Linked Data from a Secondary Analyst Perspective | Goldwyn Millar\, Statistics Canada \n15:10 – 15:40 Coffee break \n15:40 – 16:20 Design-based Conformal Prediction for Survey Sampling | Jerzy Wieczorek\, Colby College \n16:20 – 17:00 Improving Estimates from the Survey on Household Income and Wealth Using Administrative Data with Measurement Error via Structural Equation Models | Giovanna Ranalli\, Università degli Studi di Perugia \n17:00 – 17:30 Inference from Nonrandom Samples Using Bayesian Machine Learning | Yutao Liu\, Boehringer Ingelheim \nWednesday\, July 10\, 2024\nChair: Changbao Wu \n9:10 – 9:50 Data Integration with Nonprobability Sample: Semiparametric Model-assisted Approach | Sixia Chen\, University of Oklahoma \n9:50 – 10:30 QR Prediction for Statistical Data Integration | Camelia Goga\, Université de Bourgogne Franche Comté \n10:30 – 11:00 Coffee break \n11:00 – 11:40 Inference for Big Data Assisted by Small Area Methods: An Application on SDGs Sensitivity of Enterprises in Italy | Gaia Bertarelli\, Ca’ Foscari University of Venice \n11:40 – 12:10 Generalized Least Squares in Non-monotone Missing Data | Caleb Leedy\, Iowa State University \n12:10 – 12:40 Propensity Score Weighting with Post-treatment Survey Data | Wei Liang\, University of Waterloo \n12:45 Lunch
URL:https://canssi.ca/events/workshop-survey-sampling/
LOCATION:University of Ottawa\, 75 Laurier Avenue East\, Ottawa\, Ontario\, K1N 6N5\, Canada
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BEGIN:VEVENT
DTSTART;TZID=America/Vancouver:20240607T100000
DTEND;TZID=America/Vancouver:20240607T110000
DTSTAMP:20260511T023622
CREATED:20240319T033945Z
LAST-MODIFIED:20240611T194750Z
UID:24943-1717754400-1717758000@canssi.ca
SUMMARY:2024 CANSSI Town Hall
DESCRIPTION:If you’ve been meaning to explore what CANSSI can offer you\, the 2024 CANSSI Town Hall is for you. \nThe Town Hall will take place on Friday\, June 7\, from 10:00 to 11:00 a.m. PDT 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 from CANSSI Director Don Estep\, we invite you to join your colleagues from across Canada for this session. \nThis event has passed. \nWATCH THE VIDEO RECORDING \nOnce you have registered\, you will receive a Zoom link for the session via email. \nAgenda\n\nProgram changes\nNational retreat\nMentoring\nImage competition\n\nNOTE: If you are a CANSSI representative for your university\, note that the Town Hall will occur immediately after the 2024 CANSSI Annual General Meeting (AGM)\, which will take place from 9:30 to 10:00 a.m. PDT\, also on Zoom. CANSSI representatives will receive materials and a Zoom link for the AGM via email.
URL:https://canssi.ca/events/2024-town-hall/
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