Scholar
Michael Cooper
Google Scholar ID: hfNx8qUAAAAJ
PhD Student, University of Toronto; Abridge AI
Citations & Impact
Citations
162
H-index
6
i10-index
4
Publications
14
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- Published papers: 'DynaMELD: A Dynamic Model of End-Stage Liver Disease for Equitable Prioritization' (2024), 'Copula-based Deep Survival Models for Dependent Censoring' (2023), 'The Curious Language Model: Strategic Test-Time Information Acquisition' (2025). Named a Swartz-Reisman Institute for Technology and Society graduate fellow and had an internship at Abridge.
Research Experience
- As a Ph.D. student at the University of Toronto, focusing on developing clinical machine learning systems; while at Stanford, participated in several research projects, including investigating the influence of indoor built space design on human wellbeing, building an augmented reality application, and constructing a computer vision dataset comprising complex multi-object multi-actor scenes.
Education
- Ph.D. in Computer Science from the University of Toronto, advised by Rahul G. Krishnan and Michael Brudno; B.S. and M.S. degrees in Computer Science from Stanford University, where he worked with James Landay, Sarah Billington, Bruce Daniel, Ehsan Adeli, and Fei-Fei Li.
Background
- Research Interests: Designing clinical machine learning systems, particularly for national-scale, high-stakes decision-making settings like liver transplant prioritization. Also designing and studying algorithms to make modern machine learning methods more reliable and interpretable.
Miscellany
- Hobbies include scuba diving, long-distance running, alpine skiing, cheering on the Vancouver Canucks, and reading science fiction and historical non-fiction (favorites: Liu Cixin's 'Remembrance of Earth's Past Trilogy', Kim Stanley Robinson's 'Mars Trilogy', and Ben Rich and Leo James' 'Skunk Works').
