This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a McGill University directory, so their courses may be missing. Find their university profile.
Research
Latest papers
The schema spectrum: Emergent structures and levels of abstraction in AI and the brain.
Neuron · 2026
Pregnancy AI: Development and Internal Validation of an Artificial Intelligence Tool to Predict Live Births in ICSI and IVF Cycles Using Clinical Features and Embryo Images.
Medicina (Kaunas, Lithuania) · 2026
An Artificial Intelligence-Based Model to Predict Pregnancy After Intrauterine Insemination: A Retrospective Analysis of 9501 Cycles.
Journal of personalized medicine · 2025
Latest funding
- $192,000
Reinforcement Learning for Artificial Intelligence
NSERC · 2023 · Principal investigator
- $910,350
AI & Personalized Therapeutics
CIHR · 2022 · Co-investigator
- $525,000
AI for public health (AI4PH): A focus on equity and prevention
CIHR · 2019 · Co-investigator
25 publications.
The schema spectrum: Emergent structures and levels of abstraction in AI and the brain.
Samiei M, Precup D, Richards BA
Pregnancy AI: Development and Internal Validation of an Artificial Intelligence Tool to Predict Live Births in ICSI and IVF Cycles Using Clinical Features and Embryo Images.
Minano Masip J, Borduas P, Kadoch IJ, Phillips S, Precup D, Dufort D
An Artificial Intelligence-Based Model to Predict Pregnancy After Intrauterine Insemination: A Retrospective Analysis of 9501 Cycles.
Minano Masip J, Grysole C, Borduas P, Kadoch IJ, Phillips S, Precup D, Dufort D
Towards AI-designed genomes using a variational autoencoder.
Dudek NK, Precup D
Automated prediction of extubation success in extremely preterm infants: the APEX multicenter study.
Kanbar LJ, Shalish W, Onu CC, Latremouille S, Kovacs L, Keszler M, Chawla S, Brown KA, Precup D, Kearney RE, Sant'Anna GM
Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.
Falet JR, Durso-Finley J, Nichyporuk B, Schroeter J, Bovis F, Sormani MP, Precup D, Arbel T, Arnold DL
Deep learning, reinforcement learning, and world models.
Matsuo Y, LeCun Y, Sahani M, Precup D, Silver D, Sugiyama M, Uchibe E, Morimoto J
PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information.
Ahsan F, Yan Z, Precup D, Blanchette M
Fast reinforcement learning with generalized policy updates.
Barreto A, Hou S, Borsa D, Silver D, Precup D
Assessment of Extubation Readiness Using Spontaneous Breathing Trials in Extremely Preterm Neonates.
Shalish W, Kanbar L, Kovacs L, Chawla S, Keszler M, Rao S, Latremouille S, Precup D, Brown K, Kearney RE, Sant'Anna GM
Reinforcement Learning for Artificial Intelligence
Principal investigators: Precup, Doina
Keywords: Deep Neural Networks; Markov Decision Processes; Partially Observable Markov Decision Processes; Planning; Reasoning under uncertainty; Reinforcement Learning; Temporal Abstraction
AI & Personalized Therapeutics
Principal investigators: Tamblyn, Robyn M; Filion, Kristian B; McDonald, Emily G; Singer, Wendy
Keywords: Artificial Intelligence; Big Data; Machine Learning; Patient-Reported Outcomes; Personalized Medicine; Pharmacare; Pragmatic Trials; Predictive Analytics; Reinforcement Learning
AI for public health (AI4PH): A focus on equity and prevention
Principal investigators: Buckeridge, David L; Lee, Joon; Lix, Lisa M; Osgood, Nathaniel D; Rosella, Laura C
Keywords: Ai; Equity; Public Health; Summer Institute
Learning good representations for and with reinforcement learning
Principal investigators: Precup, Doina
The "Quantified Self" and the Quantified Place: Developing an Artificial Intelligence System From Smart Phone and Geo-Spatial Data to Lower Dietary and Physical Inactivity Disease Burden
Principal investigators: Ross, Nancy; Precup, Doina
Keywords: Health-Related Behaviour; Machine Learning; Nutrition; Physical Activity; Population Health; Smart Phone Sensors
Automatic segmentation of healthy tissues and tumours in patient brain images using 3D fully convolutional neural networks
Principal investigators: Arbel, Tal
McGill Science for a Sustainable Society Symposium
Principal investigators: Precup, Doina
Machine Learning
Principal investigators: Precup, Doina
Keywords: CRC
Prediction of Extubation Readiness in Extreme Preterm Infants by the Automated Analysis of CardioRespiratory Behavior
Principal investigators: Kearney, Robert E
Keywords: Cardio-Respiratopy; Extubation; Machine Learning; Patient Management; Premature Infants; Respiration
STARVING FOR SLEEP: Prevention of Childhood Obesity by Rapid Translation and Dissemination of Research via a University/School-Board Partnership
Principal investigators: Gruber, Reut; Somerville, Gail
Keywords: Children; Knowledge Translation; Nutrition; Obesity; Physical Activity; School-Based Intervention; Sleep
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Obstetrics and Gynecology
- Epidemiology, Biostatistics and Occupational Health
- Medicine
- Biomedical Engineering
- Other
Co-authors at McGill University, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
Wissam Shalish
Faculty
5 shared papers, latest 2023
Daniel Dufort
Obstetrics and Gynecology
2 shared papers, latest 2026
David Buckeridge
Medicine
1 shared papers, latest 2013
Robert Kearney
Biomedical Engineering
1 shared papers, latest 2005
Mathieu Blanchette
Faculty
1 shared papers, latest 2022
David Buckeridge
Epidemiology, Biostatistics and Occupational Health
1 shared papers, latest 2013
A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.