Portrait of Doina Precup

Doina Precup

Core Academic Member
Canada CIFAR AI Chair
Associate Professor, McGill University, School of Computer Science
Research Team Leader, Google DeepMind
Research Topics
Medical Machine Learning
Molecular Modeling
Probabilistic Models
Reasoning
Reinforcement Learning

Biography

Doina Precup combines teaching at McGill University with fundamental research on reinforcement learning, in particular AI applications in areas of significant social impact, such as health care. She is interested in machine decision-making in situations where uncertainty is high.

In addition to heading the Montreal office of Google DeepMind, Precup is a Senior Fellow of the Canadian Institute for Advanced Research and a Fellow of the Association for the Advancement of Artificial Intelligence.

Her areas of speciality are artificial intelligence, machine learning, reinforcement learning, reasoning and planning under uncertainty, and applications.

Current Students

PhD - McGill University
PhD - McGill University
PhD - McGill University
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PhD - McGill University
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PhD - McGill University
Master's Research - McGill University
PhD - McGill University
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PhD - McGill University
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Master's Research - McGill University
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Research Intern - McGill University
Research Intern - McGill University
PhD - McGill University
PhD - McGill University
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PhD - McGill University
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Master's Research - McGill University
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PhD - McGill University
PhD - McGill University
PhD - McGill University
Research Intern - McGill University
PhD - McGill University
Master's Research - Université de Montréal
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PhD - McGill University
Postdoctorate - McGill University
Master's Research - McGill University
PhD - McGill University
PhD - McGill University
Principal supervisor :
PhD - McGill University
PhD - McGill University
Master's Research - McGill University
Principal supervisor :
Master's Research - McGill University
Collaborating researcher - McGill University
Master's Research - Université de Montréal
PhD - McGill University
PhD - McGill University
Co-supervisor :
PhD - McGill University
Principal supervisor :
Postdoctorate - Université de Montréal
Principal supervisor :
PhD - McGill University
Co-supervisor :
PhD - McGill University
Master's Research - McGill University
PhD - McGill University
PhD - McGill University
Co-supervisor :
Research Intern - McGill University
Research Intern - McGill University
Undergraduate - McGill University
PhD - McGill University
PhD - McGill University
Co-supervisor :

Publications

Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation
Andrew Doyle
Douglas Arnold
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions
Teng Long
Emmanuel Bengio
Ryan Lowe
Humans interpret texts with respect to some background information, or world knowledge, and we would like to develop automatic reading compr… (see more)ehension systems that can do the same. In this paper, we introduce a task and several models to drive progress towards this goal. In particular, we propose the task of rare entity prediction: given a web document with several entities removed, models are tasked with predicting the correct missing entities conditioned on the document context and the lexical resources. This task is challenging due to the diversity of language styles and the extremely large number of rare entities. We propose two recurrent neural network architectures which make use of external knowledge in the form of entity descriptions. Our experiments show that our hierarchical LSTM model performs significantly better at the rare entity prediction task than those that do not make use of external resources.
Bayesian and grAphical Models for Biomedical Imaging
M. Cardoso
Ivor J. A. Simpson
Annemie Ribbens
Bayesian and grAphical Models for Biomedical Imaging
M. Jorge Cardoso
Ivor J. A. Simpson
Annemie Ribbens