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Aaron Courville Computer scientist

Aaron Courville’s current research interests focus on the development of deep learning models and methods. He is particularly interested in developing probabilistic models and novel inference methods. While he has mainly focused on applications to computer vision, he is also interested in other domains such as natural language processing, audio signal processing, speech understanding and just about any other artificial-intelligence-related task.


Winning Team Member of the Transfer Learning Challenge, ICML Workshop, 2011.

Winning Team Member of the Unsupervised and Transfer Learning Challenge Phase II, NIPS, 2011.

Relevant Publications

D. Erhan et al, "Why does unsupervised pre-training help deep learning?" J. Machine Learning Research, vol. 11, pp. 625-660, 2010.



Fellow Learning in Machines & Brains


Université de MontréalDepartment of Computer Science and Operations Research


PhD (Computer Science) Carnegie Mellon University

M.A.Sc. University of Toronto

B.A.Sc. (Engineering Science) University of Toronto



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