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  1. 1 de dic. de 2022 · Joelle Pineau - AI at Meta. CO-MANAGING DIRECTOR | MONTREAL, CANADA. Joelle is Vice President, AI Research at Meta and a Professor at McGill University. Her research focuses primarily on developing new models and algorithms for planning and learning in complex, partially observable domains.

  2. Joëlle Pineau (born 1974) is a Canadian computer scientist and Associate Professor at McGill University. She is the global Vice President of Facebook Artificial Intelligence Research (FAIR), now known as Meta AI, and is based in Montreal , Quebec .

  3. Joelle Pineau is a Professor and William Dawson Scholar at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She is a core academic member of Mila and a Canada CIFAR AI chairholder.

  4. 1642. 2018. How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation. CW Liu, R Lowe, IV Serban, M Noseworthy, L Charlin, J Pineau. arXiv preprint arXiv:1603.08023. , 2016. 1502. 2016. Point-based value iteration: An anytime algorithm for POMDPs.

  5. mila.quebec › en › joelle-pineauJoelle Pineau | Mila

    Joelle Pineau is a professor and William Dawson Scholar at the School of Computer Science, McGill University, where she co-directs the Reasoning and Learning Lab. She is a core academic member of Mila – Quebec Artificial Intelligence Institute, a Canada CIFAR AI Chair, and VP of AI research at Meta (previously Facebook), where she leads the ...

  6. Joelle Pineau is an Associate Professor and William Dawson Scholar at the School of Computer Science at McGill University, where she co-directs the Reasoning and Learning Lab. She is a core academic member of Mila and a Canada CIFAR AI chairholder.

  7. Joëlle Pineau is the Co-director of the Reasoning and Learning Lab in the School of Computer Science. Prof. Pineau’s research focuses on developing new models and algorithms that allow computers to learn to make good decisions in complex real-world domains, even in circumstances where there is incomplete or incorrect information.