News:

Looking for the Machine Learning Reproducibility Checklist?
Use this before your next paper submission to ensure you don't miss important details!

Current status and openings:

I currently share my time between McGill and Meta. I am not currently taking new graduate students at McGill and am not able to host international visitors or interns. McGill CS undergraduate students who have taken COMP-424 or COMP-551 are invited to contact one of my postdocs to inquire about possible research projects; contact them 2 weeks before the semester for a 3 or 4 credit research course, and in January for a summer full-time internship (positions are very limited).

Bio:

Joelle Pineau is the VP AI Research at Meta, leading its Fundamental AI Research (FAIR) team, with labs across Canada, US and Europe. She is also a Professor at the School of Computer Science at McGill University and core member of Mila. She holds a BASc in Engineering from the University of Waterloo, and an MSc and PhD in Robotics from Carnegie Mellon University. Dr. Pineau's research focuses on developing new models and algorithms for planning and learning in complex domains. She also works on applying these algorithms to real-world problems in robotics, healthcare, and conversational agents. She is a past President of the International Machine Learning Society, the inaugural Reproducibility Chair of the NeurIPS conference, and is the creator of the ML Reproducibility checklist and the ML Reproducibility challenge. She is a recipient of NSERC's E.W.R. Steacie Memorial Fellowship (2018), the Governor General's Innovation Awards (2019), a CIFAR Canada AI (CCAI) chair-holder, a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), and a Fellow of the Royal Society of Canada (RSC).