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Taylor Symposium on Applied AI

Friday, May 15, 2026
Faculty Club 3450 rue McTavish, Montreal, QC, H3A 0E5, CA

Please join us for the inaugural Taylor Symposium on Applied AI. The theme of this year鈥檚 symposium is emerging trends in artificial intelligence, with a focus on showcasing applied AI research and initiatives underway within the Faculty.

The keynote speaker is Michael Rabbat, a former 91丝瓜视频 professor in Electrical and Computer Engineering, and Co鈥慒ounder and Vice President of World Models at AMI. Please see below to learn more about the speaker and his talk.

The symposium is organized by the Faculty of Engineering and made possible through the generous support of Scott Taylor. This year鈥檚 symposium marks the first event in a symposium series that will take place every two years.

Event info and schedule:

Date: May 15, 2026

Location:听91丝瓜视频 Faculty Club (3450 Rue McTavish)

  • 8:00 Am | Registration / Breakfast
  • 8:30 AM | Welcome / Introduction
  • 8:45 - 10:00 AM |听Lightning talks:听Profs. James Clark, Warren Gross, Lili Wei, and Roni Khazaka
  • 10:00 - 11:00 AM |听Keynote presentation:听Towards AI that learns and acts with World Models by Michael Rabbat, Co-founder and VP World Models at AMI
  • 11:00 - 11:15 AM |听Coffee break
  • 11:15 AM - 12:00 PM |听Lightning talks:听Profs. Tim Xie, Jiangbo Yu, and Yi Shao
  • 12:00 - 1:00 PM | Lunch
  • 1:00 - 2:15 PM |听Lightning talks: Profs. Fiona Zhao, Audrey Sedal, Guillaume Durandau, Jozsef Kovecses, and Inna Sharf
  • 2:15 - 3:00 PM | Panel discussion
  • 3:00 - 3:15 PM | Coffee break
  • 3:15 - 4:30 PM |听Lightning talks: Profs. Roussos Dimitrakopoulos, Mustafa Kumral, Samuel Huberman, Natalie Reznikov, and Codruta Ignea
  • 4:30 PM | Closing remarks
  • 4:45 PM |听Cocktail reception
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Keynote presentation:听Towards AI that learns and acts with World Models

Keynote speaker: Michael Rabbat

In this talk, Michael Rabbat explores the next frontier in AI - World Models. He discusses how recent work on V鈥慗EPA 2 moves AI beyond simple word prediction toward systems that learn through observation of the physical world. By learning directly from video without the need for human鈥憀abeled data, this self鈥憇upervised approach offers a more efficient path toward machines that can model the underlying dynamics of their environment. He will outline how this direction enables the development of the next generation of intelligent agents鈥攕ystems that do not merely communicate, but can truly understand, plan, and act in the physical world.

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Michael Rabbat

Michael Rabbat is Co-founder and VP World Models at Advanced Machine Intelligence (AMI), where he is building a new breed of AI systems focused on understanding and reasoning about the world. He is also an Associate Industry Member at Mila. Previously, Michael was a Research Director at Meta, where he was a founding member of FAIR Montr茅al, contributing to the company's fundamental AI research efforts. Prior to that, he spent over a decade as a professor at the Department of Electrical and Computer Engineering at 91丝瓜视频. He earned his Ph.D.
Category: 
Thu, 04/30/2026 - 17:02
Source Site: 
/engineering
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