AI and Biology
9:00am-17:30pm on May 25 2026, Blusson Hall 10011
Program Overview
Registration
Breakfast
Opening Remarks
Towards generative design of DNA to direct tissue-specific gene expression for gene therapy
Wyeth Wasserman, University of British Columbia
Learning Interpretable Representations in Neural Signals with Sparse Autoencoders
Bahareh Tolooshams, University of Alberta and Amii
Coffee Break
Talk #3
Amin Emad, McGill University
Talk #4
Qihuang Zhang, McGill University
Lunch Break
Visualizing distortion in dimensionality reduction
Michael Hoffman, University of Toronto and UHN
Flow matching for cell dynamics
Lazar Atanackovic, University of Alberta and Amii
Coffee Break
Talk #8
Jiarui Ding, University of British Columbia
Talk #9
Archer Yang, McGill University
Closing Remarks
About the Workshop
The rapid advancement in AI and machine learning is transforming how we study biological systems. Myriad biomedical fields, including genomics, drug discovery, protein engineering, and medical imaging, now rely heavily on AI. At the same time, biological problems are driving new methodological developments in AI, in areas like sequence modeling, explainable AI, causal learning, and representation learning over structured spaces.
The AI and Biology workshop at AI/CRV 2026 brings together researchers working across this intersection. Topics of interest include genomics, single-cell omics and systems biology; protein engineering, synthetic biology and drug discovery; medical imaging and clinical data; as well as the underlying methodological challenges these domains present.
Speakers
Wyeth Wasserman
Professor, Medical Genetics; Vice Dean Research, Faculty of Medicine, UBC
Talk title: Towards generative design of DNA to direct tissue-specific gene expression for gene therapy
Jiarui Ding
Assistant Professor, Computer Science, University of British Columbia
Archer Yang
Associate Professor, Mathematics and Statistics, McGill University
Bahareh Tolooshams
Assistant Professor, Electrical & Computer Engineering, University of Alberta; Amii Fellow
Talk title: Learning Interpretable Representations in Neural Signals with Sparse Autoencoders
Amin Emad
Associate Professor, Electrical and Computer Engineering, McGill University
Michael Hoffman
Senior Scientist, Princess Margaret Cancer Centre (UHN); Associate Professor, University of Toronto
Talk title: Visualizing distortion in dimensionality reduction
Qihuang Zhang
Assistant Professor, Epidemiology, Biostatistics and Occupational Health, McGill University
Lazar Atanackovic
Assistant Professor, University of Alberta; Amii Fellow
Talk title: Flow matching for cell dynamics
