IFML Workshop 2023

Hosted by the Institute for Foundations of Machine Learning
University of Washington

Jointly organized with University of Texas at Austin, Wichita State University, Microsoft Research


April 20 - 22, 2023


Room 332, Husky Union Building, University of Washington, Seattle campus

Invited Speakers

Sebastien Bubeck
Microsoft Research
Rachel Ward
University of Texas at Austin
Yasaman Bahri
Google Research
Ananya Kumar
Stanford University
Alex Dimakis
University of Texas at Austin
Yejin Choi
University of Washington, AI2
Baharan Mirzasoleiman
University of Los Angeles
Denny Zhou
Google Research
Ming Lin
Amazon Research
Georgia Gkioxari
Ludwig Schmidt
University of Washington
Mengdi Wang
Princeton University


April 20

9:00-9:45 Sebastien Bubeck - MSR
9:45-10:30 Georgia Gkioxari - Caltech
10:30-11:00 Break
11:00-11:45 Alex Dimakis - UT
11:45-2:00 Lunch
2:00-2:45 Denny Zhou - Google
2:45-3:30 Baharan Mirzasoleiman - UCLA
3:30-4:00 Break
4:00-5:00 Short talks and datasets demos
5:00-7:00 Evening Buffet in University Village (Ba Bar)

April 21

9:00-9:45 Mengdi Wang - Princeton
9:45-10:30 Yasaman Bahri - Google
10:30-11:00 Break
11:00-11:45 Ludwig Schmidt - UW
11:45-2:00 Lunch
2:00-2:45 Ming Lin - Amazon
2:45-3:30 Ananya Kumar - Stanford
3:30-4:00 Break
4:00-5:00 Panel Discussion

April 22

9:30-10:00 Short talks and dataset demos
10:00-10:30 Break
10:30-11:15 Rachel Ward - UT
11:15-12:00 Yejin Choi - UW
12:00-12:30 Closing remarks

Titles and Abstracts

Review a list of titles and abstracts of the speakers outlined above here.


This workshop aims to bring together researchers to discuss emerging challenges and opportunities following the spectacular progress of platform models a.k.a. foundation models.

Registration is now closed.


Organizer: Zaid Harchaoui (UW), Atlas Wang (UT)
Local Organizers: Jillian Fisher (UW), Ronak Mehta (UW), Medha Agarwal (UW),


Questions? Contact us!