Joelle Pineau
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Joelle Pineau (born 1974) is a Canadian computer scientist known for her research in reinforcement learning, her advocacy for reproducibility in machine learning, and her leadership of Meta's Fundamental AI Research organization. She is a professor and William Dawson Scholar at the School of Computer Science at McGill University and a core academic member of Mila, the Quebec Artificial Intelligence Institute. From 2017 to 2025 she worked at Meta (formerly Facebook), where she eventually served as Vice President of AI Research and led the Meta FAIR lab. In August 2025 she was named the first Chief AI Officer of Cohere.[1][2][3]
Pineau was born in 1974 in Ottawa, Ontario.[1] She earned a Bachelor of Applied Science in systems design engineering from the University of Waterloo, then completed a Master of Science and a PhD in robotics at Carnegie Mellon University, receiving her doctorate in 2004.[1][2][3] At Carnegie Mellon she was advised by Sebastian Thrun and Geoffrey Gordon. Her doctoral work concerned planning in partially observable Markov decision processes (POMDPs), a framework for sequential decision-making under uncertainty, and a chapter from that work became one of her most-cited contributions.[1]
Pineau joined McGill University as a faculty member in the School of Computer Science, where she co-directs the Reasoning and Learning Lab.[2][3] She holds the title of William Dawson Scholar and is a Canada CIFAR AI Chair.[2][3] As a core academic member of Mila, she is part of one of the largest concentrations of deep-learning researchers in the world.[2]
Her research develops models and algorithms for planning and learning in complex, partially observable domains. The work spans reinforcement learning, deep learning, and Bayesian methods for planning under uncertainty, with applications to robotics, conversational agents (dialogue systems), games, and health care, including personalized medicine.[2][3] One line of her health-care research applied reinforcement learning and adaptive methods to treatment strategies, for example optimizing therapy decisions over time.[3]
Pineau has held several service roles in the machine-learning community. She has served as a past president of the International Machine Learning Society, which oversees the International Conference on Machine Learning (ICML), and has sat on the editorial board of the Journal of Machine Learning Research.[2][3]
Pineau is one of the most prominent advocates for reproducibility in machine learning research. In 2019 she served as the inaugural Reproducibility Chair of the Conference on Neural Information Processing Systems (NeurIPS), where she introduced the Machine Learning Reproducibility Checklist into the paper-submission process.[1][3] The NeurIPS 2019 reproducibility program had three components: a code-submission policy, a community-wide reproducibility challenge, and the checklist itself.[4]
She and her collaborators documented the program in a 2020 report titled 'Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)', on which she was the first author.[4] Her group also studied reproducibility empirically, including an analysis of how implementation details and random seeds affect reported results in deep reinforcement learning. The reproducibility checklist she helped create has been reused at subsequent NeurIPS conferences and adapted by other venues.[4]
In 2017 Pineau joined Facebook (later Meta) to lead its newly opened FAIR laboratory in Montreal, while remaining on the McGill faculty.[1][2] FAIR, the Fundamental AI Research organization, was founded under Yann LeCun and conducts open, long-horizon research in artificial intelligence.
In early 2023 Pineau was promoted to lead the entire FAIR organization as Vice President of AI Research, reporting to Meta's Chief Product Officer Chris Cox.[5][6] During her time leading the lab, FAIR's outputs included the open-source Llama family of large language models and the PyTorch deep-learning framework, and she helped guide the early development of Meta's open models alongside LeCun.[1][7]
On April 1, 2025, Pineau announced in a post on social media that she would leave Meta, with her last day in May 2025, after roughly eight years at the company.[5][6][8] She said she planned to take time off before pursuing a new opportunity.[8] Her departure was reported in the context of Meta's broader reorganization of its AI efforts, including the assembly of a new team focused on advanced AI.[7]
On August 14, 2025, Cohere, a Toronto-based company that builds large language models for enterprise use, announced that Pineau would join as its first Chief AI Officer, a newly created role.[7][9] In the position she oversees AI strategy across the company's research, product, and policy teams, including Cohere Labs, the firm's research division.[7][9] Reporting indicated she would begin in the role around September 2025.[9]
The appointment was announced alongside Cohere's US$500 million funding round, which valued the company at US$6.8 billion, up from a US$5.5 billion valuation the previous year; the round was led by the Canadian funds Radical Ventures and Inovia Capital, with participation from investors including AMD Ventures, Nvidia, and others.[9] In interviews around the hiring, Pineau distinguished Cohere's enterprise focus from the emphasis on artificial general intelligence at some other labs, saying she was 'interested in real solutions, rather than a lot of talk and the hype.'[9]
| Year | Honor |
|---|---|
| 2018 | Fellow, Association for the Advancement of Artificial Intelligence (AAAI) |
| 2018 | NSERC E.W.R. Steacie Memorial Fellowship |
| 2019 | Governor General's Innovation Award |
| 2023 | Fellow, Royal Society of Canada |
| Period | Role |
|---|---|
| 2004 | PhD in robotics, Carnegie Mellon University |
| 2004 onward | Professor, School of Computer Science, McGill University; co-director, Reasoning and Learning Lab |
| 2017 to 2025 | Facebook / Meta: led the FAIR Montreal lab (from 2017), then VP of AI Research leading all of FAIR (from early 2023) |
| 2019 | Inaugural Reproducibility Chair, NeurIPS |
| 2025 | Chief AI Officer, Cohere |