Description:

This one-day symposium aims to encourage collaborations, tighten the relationship, and strengthen the connections for female researchers in theoretical machine learning, computer science, applied mathematics, and statistical inference. We offer an opportunity and friendly environment to enhance professional skills and encourage participants from graduate students, postdocs, professors, and researchers from the industry. The event will be held virtually; we welcome participants worldwide.

Speaker List:

• Jelena Diakonikolas (University of Wisconsin-Madison)
• Stefanie Jegelka (Massachusetts Institute of Technology)
• Po-Ling Loh (University of Wisconsin-Madison)
• Caroline Uhler (Massachusetts Institute of Technology)
• Rachel Ward (University of Texas at Austin)

Time and Schedule:

Friday, April 9th, 2021, from 10:30 a.m. to 5:30 p.m. CST. Schedule is released here.

The workshop will be held virtually. The talks and the panel discussion will be on zoom and the social hour will be on teamflow. To receive information on how to join the event, please register using the link below.

Sponsors:

• Toyota Technological Institute at Chicago (TTIC)
• Women and Mathematics Program in Institute for Advanced Studies (IAS)
• Institute for Mathematical and Statistical Innovation (IMSI)

Organizers:

Mina Karzand (TTIC) and Xiaoxia Wu (TTIC and U Chicago)
Advisor: Rebecca Willett (U Chicago)

If you have any questions regarding the symposium, please contact xwu@ttic.edu or mina@ttic.edu

Register

The Women in Theoretical Machine Learning Symposium is partnered with The Multifaceted Complexity of Machine Learning by IMSI on April 12-16, 2021.