UOttawa Math+Stat Colloquium

Welcome to the University of Ottawa Colloquium in Mathematics and Statistics (UOCMS). This series brings together researchers from diverse institutions to present lectures on current developments in mathematics and statistics. A colloquium talk is one that is geared towards a general mathematical audience.

We proudly acknowledge the support of the Department of Mathematics and Statistics, the Tutte Institute for Mathematical Computing (TIMC) and the Centre de recherches mathématiques (CRM).

Next talk: Stacey Smith? (University of Ottawa) October 2, 2026

Education Colloquium

Title: Can a large life-sciences calculus class benefit from being flipped?

Prof Smith? (the question mark is part of her name) is a Professor in the Department of Mathematics and Statistics and is cross-appointed to the School of Epidemiology and Public Health of the Faculty of Medicine. Her research centers on the mathematical modeling of infection diseases. She is a prolific author and a gifted public speaker, with dozens of high-profile media appearances through which she advocates (often with a touch of humour) for mathematical research.

Abstract: Recent educational theory emphasizes the benefits of flipped-classroom courses, which actively support the development of complex metacognitive skills and allow both students and instructors greater flexibility in tailoring the learning process to individuals. With the advent of AI, classroom teaching needs to change, and change quickly. However, flipping a large classroom without additional resources requires adapting strategies from smaller flipped classrooms, and the effects of these strategies at larger scales have not been explored for STEM courses. We implemented flipped-classroom techniques in one section of a large-scale undergraduate Calculus for the Life Sciences course. We then compared final exam results between course sections, and built a predictive model to understand how flipped-classroom techniques influence student success. While course averages were not significantly different across sections, high-achieving students in the flipped-classroom section were more successful at solving higher-complexity problems than their high-achieving peers in traditionally taught sections. However, lower-achieving flipped-classroom students struggled more than their lower-achieving peers at rote problem-solving tasks. Flipping a large classroom appears to improve learning of higher-complexity strategic skills, but it may come at the cost of deeper conceptual understanding for some students. Instructors of larger-scale courses should balance these priorities while designing and teaching a flipped-classroom STEM course.

Some upcoming speakers:

Bei Jiang (University of Alberta) October 30, 2026

This talk will be part of the SCOPE seminar and is supported by CANSSI

Prof. Jiang is an Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, a Canada CIFAR AI Chair, and a Fellow of the Alberta Machine Intelligence Institute. Professor Jiang received her PhD in Biostatistics from the University of Michigan and her MSc in Biostatistics from the University of Alberta. Her research develops statistical and machine-learning methods for complex health data, with particular interests in Bayesian hierarchical modelling, functional and imaging data analysis, kernel methods, and the joint modelling of longitudinal and health outcomes.

Alain Valette (University of Neuchatel) November 9, 2026

Prof Valette earned his PhD under the supervision of Lucien Waelbroeck and Alain Connes. He has a long and distinguished history of important mathematical contributions, in a large range of areas including operator algebras, graph theory and geometric group theory. He has written several books with different coauthors, notably on Kazhdan's Property (T), expanding graphs and the Baum-Connes conjecture. These reference books have been crucial in the modern development of these topics.

Chris Kapulkin (Western University) November 20, 2026

Prof Kapulkin earned his PhD from the University of Pittsburgh in 2014. Dr.~Kapulkin works in homotopy theory, applying its techniques to numerous other areas of mathematics, including formal logic, theoretical computer science, combinatorics, category theory, and interactive theorem proving. He has made a number of significant contributions to homotopy type theory, including proving the homotopy canonicity conjecture first proposed by Voevodsky in 2010. He won the Florence Bucke Prize in Science in 2024 and the Coxeter--James Prize of the Canadian Mathematical Society in 2025, and is an Associate Editor of the Canadian Journal of Mathematics and the Canadian Mathematical Bulletin.

Archer Yang (McGill) November 27, 2026

Prof. Yang is an Associate Professor of Statistics at McGill University and an Associate Academic Member of Mila, the Quebec AI Institute. He is also affiliated with McGill’s programs in Computer Science and Quantitative Life Sciences. Professor Yang received his PhD from the University of Minnesota, where he was advised by Professor Hui Zou. His research lies at the intersection of statistical machine learning and uncertainty quantification, with interests spanning high-dimensional inference, reliable AI, scalable computational methods, and biomedical data science, including applications to drug discovery.

Emily Riehl (Johns Hopkins) February 2027

Prof Riehl earned her PhD from the University of Chicago in 2009. She is the Kelly Miller Professor of Mathematics at Johns Hopkins University, working on higher category theory, homotopy type theory, and computer formalization. She has held prestigious visiting positions all over the world. She has held numerous distinctions and awards, and most recently was an invited sectional speaker in topology at the 2026 ICM. She is a community leader, having served as a founding board member of Spectra, and currently serving on the Executive of the AMS Council.

Mathilde Gerbelli-Gauthier (University of Toronto) Winter term 2027

Prof Gerbelli-Gauthier earned her PhD from the University of Chicago in 2020 and is now an Assistant Professor at the University of Toronto, working in number theory and representation theory. She is an excellent public speaker and has already won numerous distinctions for both her research and teaching. In addition to her contributions to asymptotic and statistical aspects of automorphic representations, and the cohomology of arithmetic groups, she is active in the community, organizing conferences and seminars, and serving on panels and conducting outreach activities.

Would you like to nominate a speaker? Please contact Monica Nevins, Arian Novruzi or Dingke Tang.

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