Team
Core Professors
David Rolnick
Machine Learning Theory, Climate Change, AI For Good
Doina Precup
Reinforcement Learning, Reasoning and planning under uncertainty
Jackie Chi Kit Cheung
NLP, Summarization, Computational Semantics
Joelle Pineau
Reinforcement Learning, NLP, Dialog
Prakash Panangaden
Machine Learning, Quantum Information Theory, Probabilistic Systems
Reihaneh Rabbany
Machine Learning, Knowledge Graphs
Siamak Ravanbakhsh
Machine Learning, Learning on Graphs, Generative Models, Probabilistic Models
Siva Reddy
Natural language Processing, Probabilistic Models, Reasoning
Affiliated Professors
Marc G. Bellemare
Reinforcement Learning, Representation Learning, Exploration
Nicolas Le Roux
Machine Learning, Neural Networks, Optimization and Large-Scale Learning
Timothy J O'Donnell
Natural Language Processing, Linguistics, Cognitive Science
Postdoctoral Fellows
Samira Ebrahimi Kahou
Deep learning, Multimodal learning, Reasoning, RL, Metalearning
Susan Amin
reinforcement learning, exploration, statistical physics, polymer physics
Supervised by: Doina Precup
Ph.D. Students
Aarash Feizi
Deep Learning, Vision, Graph Representation Learning
Supervised by: Reihaneh Rabbany, Adriana Romero Soriano
Aishik Chakraborty
Deep Learning, Multitask and Transfer Learning, NLP
Supervised by: Jackie Chi Kit Cheung
Andre Cianflone
Natural Language Processing, Deep Learning, Reinforcement Learning
Supervised by: Jackie Chi Kit Cheung
Arushi Jain
Reinforcement Learning, Temporal abstractions, AI Safety, Risk-minimization, Stochastic Approximation
Supervised by: Doina Precup, Pierre-Luc Bacon
Ayush Jain
Reinforcement Learning, Hierarchical RL, Skill-based learning
Supervised by: Doina Precup
Bogdan Mazoure
Deep RL, representation learning, probabilistic modeling, variational inference
Supervised by: Doina Precup, Devon Hjelm
Clara Lacroce
Learning Automata, RNN, Hankel Operators
Supervised by: Prakash Panangaden, Doina Precup
Faizy Ahsan
Genetics, Deep Learning, Graphical Models
Supervised by: Mathieu Blanchette, Doina Precup
Haque Ishfaq
Exploration in RL, Bandits, Learning Theory, TCS, Concentration inequalities, high-dimensional probability
Supervised by: Doina Precup
Harry Mingde Zhao
Reinforcement Learning, Neuro-Inspired AI
Supervised by: Doina Precup, Yoshua Bengio
Ian Porada
Representation Learning, Natural Language Understanding, Common Sense
Supervised by: Jackie Chi Kit Cheung
Jad Kabbara
Natural Language Generation, Computational Pragmatics, Deep Learning
Supervised by: Jackie Chi Kit Cheung
Joey Bose
Generative Modelling, Adversarial Machine Learning, and Meta Learning at the intersection of structured data such as language, graphs and images.
Supervised by: Prakash Panangaden
Jonathan Lebensold
Privacy-Preserving ML, Differential Privacy, Reinforcement Learning, Transfer, Healthcare
Supervised by: Doina Precup, Borja Balle
Khimya Khetarpal
Artificial Intelligence, Reinforcement Learning, Attention, Abstractions, Continual RL, Cogsci, Robotics
Supervised by: Doina Precup
Koustuv Sinha
Natural Language Understanding, Systematicity & Logic in NLU, Dialog Systems
Supervised by: Joelle Pineau
Kushal Arora
Reinforcement Learning, Manifold Learning, Compositionality and Representation learning for languages, NLP
Supervised by: Doina Precup, Jackie Chi Kit Cheung
Lianna Hambardzumyan
Analysis of Boolean functions, Computational Complexity, Combinatorics
Supervised by: Hamed Hatami
Malik H. Altakrori
Authorship Analysis, Text Mining, Machine Learning, NLP, and Deep Learning
Supervised by: Jackie Chi Kit Cheung, Benjamin Fung
Mandana Samiei
Reinforcement Learning, Meta-learning, Developmental learning, Neuroscience
Supervised by: Doina Precup, Blake Richards
Martin Gerdzhev
robotics, autonomous systems and vehicles, machine learning, deep learning, inverse reinforcement learning
Supervised by: Joelle Pineau
Maziar Gomrokchi
Privacy-Preserving RL, Adversarial Privacy Attacks in Deep RL, Reinforcement Learning, Differential Privacy, Exploration-Exploitation Trade-Off
Supervised by: Doina Precup
Melissa Mozifian
deep reinforcement learning, transfer and meta-learning, imitation learning
Supervised by: Joelle Pineau, David Meger
Neda Etebari Alamdari
Reinforcement Learning, Machine Learning, Optimization, Revenue Management
Supervised by: Doina Precup, Gilles Savard
Neil Girdhar
causal models, deep learning, representation learning, energy-based models
Supervised by: Doina Precup
Nishanth Anand
Temporal credit assignment, Reinforcement Learning Theory, Deep Reinforcement Learning
Supervised by: Doina Precup
Priyesh Vijayan
Representation learning, Deep learning, Multi-View learning, Social Networks and NLP
Supervised by: Will Hamilton
Raymond Chua
neuroscience, reinforcement learning, continual learning, hippocampal and artificial replay
Supervised by: Doina Precup, Blake Richards
Riashat Islam
Reinforcement Learning, Sample Complexity, Optimization Methods; Bayesian and Probabilistic Graphical Models, Information Theory
Supervised by: Doina Precup
Safa Alver
Lifelong Reinforcement Learning, Model-Based Reinforcement Learning
Supervised by: Doina Precup
Sahand Rezaei-Shoshtari
Deep RL, Hierarchical RL, Robotics, Representation Learning
Supervised by: Doina Precup, David Meger
Samin Yeasar Arnob
Deep Reinforcement learning, Imitation Learning, Inverse reinforcement learning
Supervised by: Doina Precup
Sitao Luan
Reinforcement Learning, Graph Networks, Planning, Matrix Computation
Supervised by: Doina Precup, Xiao-Wen Chang
Tianyu Li
machine learning, reinforcement learning, time series, system dynamics
Supervised by: Doina Precup
Veronica Chelu
reinforcement learning, lifelong learning, predictive models
Supervised by: Doina Precup
Wesley Chung
reinforcement learning, policy optimization, continual learning
Supervised by: Doina Precup, David Meger
M.Sc. Students
Akshatha Arodi Nagaraja
Natural Language Processing, Theory of Mind, Deep learning
Supervised by: Jackie Chi Kit Cheung
Albert Orozco Camacho
Network Science, Natural Language Processing, Deep Learning, Game Theoretic RL, Graph Representation Learning, Applications of RL, AI Theory
Supervised by: Reihaneh Rabbany
Amirhossein Kazemnejad
NLP, Out-of-Distribution Generalization, Contrastive Representation Learning
Supervised by: Siva Reddy
Andrei Mircea Romascanu
Natural Language Processing, Reinforcement Learning
Supervised by: Jackie Chi Kit Cheung, Doina Precup
Anthony G.X. Chen
reinforcement learning, neuroscience, deep reinforcement learning, generalization, transfer
Supervised by: Joelle Pineau, Blake Richards
Barleen Kaur
Machine learning, deep learning, transfer learning, generative models
Supervised by: Doina Precup, Tal Arbel
Cesare Spinoso-Di Piano
Biomedical natural language processing
Supervised by: Jackie Chi Kit Cheung, Samira Rahimi
Charlotte Ding
network science, graph representation learning, disease modelling
Supervised by: Reihaneh Rabbany
Chen-Yang Su
Inverse Reinforcement Learning, Imitation Learning, Causal Inference, Statistical Genetics, Machine Learning Applications to Healthcare
Supervised by: Joelle Pineau, Brent Richards
Deepak Sharma
causal inference, large-scale probabilistic inference, generative models, reinforcement learning, applications to healthcare and finance
Supervised by: Joelle Pineau, Audrey Durand
Dora Jambor
graph representation learning, meta-learning, logical rule induction, natural language processing
Supervised by: Joelle Pineau, William Hamilton
Etienne Denis
Inductive learning, graph representation learning, relational inference, neural knowledge graphs, language transformers, graph neural networks
Supervised by: William Hamilton
Gabriela Moisescu-Pareja
Reinforcement Learning, Deep Learning, Graph Representation Learning, ML Theory
Supervised by: Doina Precup
Gandharv Patil
Bayesian Inference, Optimization and Statistical Learning Theory
Supervised by: Doina Precup, Jeremy Cooperstock
Jiapeng Wu
natural languag reasoning, knowledge graph representation
Supervised by: Jackie Chi Kit Cheung, William Hamilton
Joshua Holla
Reinforcement Learning, Deep Learning, Transfer Learning
Supervised by: Doina Precup, David Meger
Jules Gagnon-Marchand
nlp, unsupervised learning, generative models, transfer learning, transformer model improvements, abstractive question answering
Supervised by: Jackie Chi Kit Cheung
Junhao Wang
Deep sets, intersection between RL and graph representation learning
Supervised by: Reihaney Rabbany, Doina Precup
Mohammad Amini
DRL, Model Based RL, planning, imitation learning, representation learning, transfer learning, hierarchical learning, Model Ensembles
Supervised by: Doina Precup
Nadeem Ward
Reinforcement learning, learning representations, optimization
Supervised by: Doina Precup
Shenyang(Andy) Huang
Anamoly Detection in Temporal graph, Tensor Decomposition, Continual Learning / Lifelong Learning, Neural Architecture Search / AutoML, Deep Learning
Supervised by: Reihaneh Rabbany, Guillaume Rabusseau
Sékou-Oumar Kaba
Deep learning, equivariance, physics, chemistry, molecules, materials, quantum mechanics, dynamical systems
Supervised by: Siamak Ravanbakhsh
Ximeng Mao
deep learning, generative model, reinforcement leanring
Supervised by: Joelle Pineau, Shirin A. Enger
Alumni
- Gavin McCracken, MSc, 2021,
- Ali Emami, PhD, 2021, Assistant Professor, Brock University
- Florence Clerc, PhD, 2021,
- Amy Zhang, PhD, 2021, Assistant Professor @ UT Austin
- Eric Crawford, PhD, 2021,
- Joshua Romoff, PhD, 2021,
- Alika Utepova, MSc, 2020,
- Vincent Luczkow, MSc, 2020, PhD student at McGill University
- Ariella Smofsky, MSc, 2020,
- Ryan Lowe, PhD, 2020, Member of Technical Staff, OpenAI
- Philip Amortila, MSc, 2019, PhD student at University of Illinois
- Zafarali Ahmed, MSc, 2019, Research Engineer, DeepMind
- Audrey Durand, Postdoc, 2019, Assistant Professor at University of Laval
- Nicolas Angelard-Gontier, MSc, 2018, PhD student @ Mila / Polytechnique Montreal
- Herke Van Hoof, Postdoc, 2018, Assistant Professor at University of Amsterdam
- Nicolas Gagné, MSc, 2018, PhD at Universite de Montreal
- Pierre-Luc Bacon, PhD, 2018, Assistant Professor at University of Montreal
- Guillaume Rabusseau, Postdoc, 2018, Assistant Professor at University of Montreal
- Pascale Gourdeau, MSc, 2017, DPhil student at University of Oxford
- Negar Ghourchian, PhD, 2017, Research Scientist at Aerial.ai
- Bénédicte Leonard-Cannon, MSc, 2016, Software Engineer at Microsoft
- Laurent Charlin, Postdoc, 2016, Assistant Professor of statistics at HEC Montréal
- Boyu Wang, PhD, 2016, Postdoc at Princeton Neuroscience Institute
- Lucas Lehnert, MSc, 2016, Ph.D. student at Brown University
- Gheorghe Comanici, PhD, 2016, Software Engineer at Google Montreal
- Gabriel Forgues, MSc, 2015, Software Engineer at Facebook Seattle
- Andrew Sutcliffe, MSc, 2015,
- Melanie Lyman-Abramovitch, MSc, 2015,
- Borja Balle, Postdoc, 2015, Lecturer at Lancaster University
- Angus Leigh, MSc, 2015, Software Engineer at Google X
- Mahdi Milani Fard, PhD, 2014, Software Engineer at Google Mountain View
- Yuri Grinberg, PhD, 2014, National Research Council Canada
- Jinxu Jia, MSc, 2014, Software Engineer at Microsoft Seattle
- Nastaran Jafarpour, PhD, 2014, Data Scientist at Via Science, Montreal
- Hiu Kim Yuen, MSc, 2014, Software Engineer at LoopPulse, Hong Kong
- Hang Ma, MSc, 2014, Ph.D. student at University of Southern California
- Clement Gehring, MSc, 2014, Ph.D. student at MIT
- Ouais Alsharif, MSc, 2014, Software Engineer at Google Mountain View
- Will Hamilton, MSc, 2014, Senior Quantitative Researcher at Citadel LLC.
- Robert D. Vincent, PhD, 2014, Teacher at Vanier College
- Andre M.S. Barreto, Postdoc, 2013, Research Scientist at Google Deepmind
- Amir-massoud Farahmand, Postdoc, 2013, Machine Learning Researcher at Mitsubishi Electric Research Laboratories
- Beomjoon Kim, MSc, 2013, Ph.D. student at MIT
- Athena K. Moghaddam, MSc, 2013, Software Engineer at Facebook Menlo Park
- Cosmin Paduraru, PhD, 2013, Postdoctoral fellow in COSMO Lab
- Sylvie C.W. Ong, Postdoc, 2013, Software Engineer at Nuance Communications Montreal
- Guillaume Saulnier Comte, MSc, 2013, Software Engineer at Google Seattle
- Danesh Ghafoorzadehnobar, MSc, 2013, Software Engineer at Microsoft in Redmond, Washington
- Gheorghita Catalin Bordianu, MSc, 2012, Software Engineer at 500px
- Jordan Frank, PhD, 2012, Software Engineer at Facebook Seattle
- Shaowei Png, MSc, 2011, Software Engineer in Google Seattle/Kirkland
- Pablo Samuel Castro, PhD, 2011, Software Engineer at Google Montreal
- Amin Atrash, PhD, 2011, Postdoc at the School of Computer Science at USC
- Susan Shortreed, Postdoc, 2011, Assistant Scientific Investigator at Group Health Research Institute
- Ryan Faulkner, MSc, 2010, Research Scientist at Google DeepMind
- Keith Bush, Postdoc, 2010, Assistant Professor of Computer Science, University of Arkansas at Little Rock
- Julien Villemure, MSc, 2010,
- Robert Kaplow, MSc, 2010, Software Engineer at Google Montreal
- Robert West, MSc, 2010, Ph.D. student, Stanford University
- Arthur Guez, MSc, 2010, Research Scientist at Google DeepMind
- Monica Dinculescu, MSc, 2010, Software Engineer at Google Mountain View
- Philippe Chaput, MSc, 2009, Lecturer, John Abbott College
- Sophia Knight, MSc, 2009, Assistant Professor, University of Minnesota Duluth
- Caitlin Philips, MSc, 2009, Google Montreal
- Norm Ferns, PhD, 2008, Research Scientist, SportLogic
- Stéphane Ross, MSc, 2008, Software Engineer at Google X
- Jonathan Taylor, MSc, 2008,
- Marc Bellemare, MSc, 2007, Research Scientist at Google DeepMind
- Masoumeh Izadi, PhD, 2007, R&D manager in sport analytics at Broadcast Solutions in Singapore
- Bohdana Ratitch, PhD, 2005, Scientific Advisor at Quintiles
- Danielle Azar, PhD, 2004, Lebanese American University
- Jacob Eliosoff, MSc, 2003,
- Martin Stolle, MSc, 2003, Software Engineer at Google Zurich
- Francois Rivest, MSc, 2002, Assistant Professor at the Royal Military College of Canada
- William Renner, MSc, 2002,
- Josée Desharnais, PhD, 1999, Full Professor, University of Laval