Research talk

Universalizing weak supervision

June 7, 2024 | 12:00 PM - 1:00 PM Pacific Time

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During this research talk, you’ll see how researchers are pushing the boundaries of what’s possible with weak supervision.

PhD Student Changho Shin from the University of Wisconsin-Madison will discuss how a new weak supervision framework allows users to apply the technique across task types without extensive customization—and even extend weak supervision to previously inaccessible label types, such as ranking.

The talk will address:

  • How weak supervision scales labeling efforts.
  • How this new framework eases transitions between task types.
  • How the new framework allows weak supervision to apply to new task types.

Presented by


Changho Shin

PhD Student
University of Wisconsin-Madison

Changho Shin is a fourth-year Ph.D. student in the Department of Computer Science at University of Wisconsin-Madison, advised by Frederic Sala. His research centers on data-centric AI and foundation models. Changho's focus is on developing efficient methods for creating and curating data for foundation models; he is the recipient of multiple awards for work in this area. Changho is a 2024 Qualcomm Innovation Fellowship Finalist.

We look forward to seeing you!

Register now