Machine learning, representation learning, deep learning, temporal database, artificial intelligence, probabilistic models, statistical models, neural networks, computer vision, data science, natural-language processing (NLP)


Yoshua Bengio is a Canadian researcher specializing in artificial intelligence, and a pioneer in deep learning. He was born in France in 1964, studied in Montreal, obtained his Ph.D. in Computer Science from McGill University in 1991, and completed post-doctoral studies at MIT.

Since 1993, he has been Professor in the Department of Computer Science and Operational Research at the Université de Montréal. He is also the Scientific Director of Mila, Scientific Director at IVADO and Canada Research Chair in Statistical Learning Algorithms.

His research on AI earned him the Urgel-Archambault Prize in 2009, followed in 2017 by the Marie-Victorin Prize, and in 2019 by the Killam Prize and the A.M. Turing Award. He is Co-director of the CIFAR Learning in Machines & Brains Program. His main research ambition is to understand the principles of learning that yield intelligence.

He supervises a large group of graduate students and post-doctoral fellows. Dr. Bengio’s research is widely cited (over 220,000 citations found by Google Scholar in October 2019, with an H-index over 149, and rising fast).

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CIRANO Publications by Yoshua Bengio

As an author

1 to 5 of 23 results

Spectral Dimensionality Reduction

Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet and 1 other authors


Learning from Partial Labels with Minimum Entropy

Yves Grandvalet and Yoshua Bengio


Locally Weighted Full Covariance Gaussian Density Estimation

Yoshua Bengio and Pascal Vincent


Manifold Parzen Windows

Yoshua Bengio and Pascal Vincent


Estimation de densité conditionnelle lorsque l'hypothèse de normalité est insatisfaisante

Julie Carreau and Yoshua Bengio

Inequality and Distribution of Income