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DTSTART;TZID=America/Halifax:20250404T120000
DTEND;TZID=America/Halifax:20250404T130000
DTSTAMP:20260407T120713
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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
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BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20250307T120000
DTEND;TZID=America/Halifax:20250307T130000
DTSTAMP:20260407T120713
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
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BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20250131T120000
DTEND;TZID=America/Halifax:20250131T130000
DTSTAMP:20260407T120713
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
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BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20241129T120000
DTEND;TZID=America/Halifax:20241129T130000
DTSTAMP:20260407T120713
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
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BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20241025T120000
DTEND;TZID=America/Halifax:20241025T130000
DTSTAMP:20260407T120713
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
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BEGIN:VEVENT
DTSTART;TZID=America/Halifax:20240927T120000
DTEND;TZID=America/Halifax:20240927T130000
DTSTAMP:20260407T120713
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/Vancouver:20240524T093000
DTEND;TZID=America/Vancouver:20240524T133000
DTSTAMP:20260407T120713
CREATED:20240525T012629Z
LAST-MODIFIED:20240525T013447Z
UID:25583-1716543000-1716557400@canssi.ca
SUMMARY:Florence Nightingale Day 2024 in Atlantic Canada
DESCRIPTION:Florence Nightingale 2024 in Atlantic Canada will take place at the University of New Brunswick Saint John on May 24\, 2024. \nCANSSI Atlantic will host this event\, which gives high school students the chance to explore studies and careers in statistical sciences. \nSchedule\n9:30–9:45 a.m. Registration Name tags and T-shirts \n9:45–10:00 a.m. | Welcome | Introductions | Who is Florence Nightingale? \n10:00–10:45 a.m. | Interactive Activity 1 (M&M Activity) \n10:45–11:15 a.m. | Campus Tour \n11:15 a.m.–12:00 p.m. | Panel (Phil Munz\, Joanna Mills Flemming\, Anson Green\, Maggie Brown) \n12:00–12:30 p.m. | Lunch \n12:30–1:15 p.m. | Interactive Activity 2 (Statistical Ecology) \n1:15–1:30 p.m. | Wrap-Up \nAbout Florence Nightingale Day\nFlorence Nightingale Day was launched in the U.S. in 2018. Since then\, it has become an international one-day initiative with in-person activities for local high school students organized at colleges and universities and virtual activities for students from all over the world. In the U.S.\, it has been celebrated at a number of institutions\, including Ohio State University\, Harvard University\, and the University of Texas at Dallas. In Canada it has been celebrated at Simon Fraser University and at the University of Toronto (co-sponsored by CANSSI Ontario). CANSSI is a major co-sponsor and co-organizer of Florence Nightingale Day together with the Caucus for Women in Statistics and the American Statistical Association. It’s part of our developing effort to attract under-represented and disadvantaged high school students to study statistical sciences. Our vision is to expand Florence Nightingale Day to become a national event involving high school students across Canada. \nIn 2024\, CANSSI will support events at Simon Fraser University\, the University of Toronto\, and potentially other universities. Our goal is to expand the number of sites each year. Check out these photos from the Florence Nightingale Day 2023 celebration organized by CANSSI and the Department of Statistics and Actuarial Science at SFU. \nFor an international list of upcoming Florence Nightingale Day celebrations\, visit this page.
URL:https://canssi.ca/events/fn-day-2024-atlantic-canada/
LOCATION:Nova Scotia
CATEGORIES:CANSSI Atlantic
ATTACH;FMTTYPE=image/png:https://canssi.ca/wp-content/uploads/FN-Day-Atlantic-2024.png
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