Joelle Pineau
Appointment
Advisor
Canada CIFAR AI Chair
Learning in Machines & Brains
Pan-Canadian AI Strategy
About
Joelle Pineau is an advisor in CIFAR’s Learning in Machines & Brains program and a Canada CIFAR AI Chair at Mila. Pineau is an associate professor at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She also leads the Facebook AI Research lab in Montreal, Canada.
Her research focuses on developing new models and algorithms for planning and learning in complex, partially observable domains. She also works on applying these algorithms to complex problems in robotics, health care, games and conversational agents. Pineau serves on the editorial board of the Journal of Artificial Intelligence Research and the Journal of Machine Learning Research and is currently president of the International Machine Learning Society.
Awards
- Governor General's Innovation Awards, 2019
- NSERC E.W.R. Steacie Memorial Fellowship, 2018
- Facebook Research Award, 2017
- Member of the College of New Scholars, Artists and Scientists, Royal Society of Canada, 2016
- William Dawson Scholar, McGill University, 2015
Relevant Publications
Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., & Meger, D. (2018, April). Deep reinforcement learning that matters. In Proceedings of the AAAI conference on artificial intelligence (Vol. 32, No. 1).
Serban, I., Sordoni, A., Lowe, R., Charlin, L., Pineau, J., Courville, A., & Bengio, Y. (2017). A hierarchical latent variable encoder-decoder model for generating dialogues. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 31, No. 1).
Serban, I., Sordoni, A., Bengio, Y., Courville, A., & Pineau, J. (2016). Building end-to-end dialogue systems using generative hierarchical neural network models. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 30, No. 1).
Liu, C. W., Lowe, R., Serban, I. V., Noseworthy, M., Charlin, L., & Pineau, J. (2016). How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation.
Pineau, J., Gordon, G., & Thrun, S. (2003). Point-based value iteration: An anytime algorithm for POMDPs. In IJCAI (Vol. 3, pp. 1025-1032).
Support Us
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.