CSL Master Calendar

MONDAY, MARCH 9TH – 4:00-5:00PM

Location: CSL Room 141

Speaker: Raymond A. Yeh, Assistant Professor, Computer Science Department, Purdue University

Abstract: While modern computer vision has traditionally prioritized benchmark accuracy, this talk advocates for a shift "beyond task performance." We explore this transition through two directions: model immunization and equivariance. First, we introduce model immunization as a defensive strategy designed to safeguard models against unauthorized fine-tuning, i.e., preserving intended behaviors against downstream manipulation. We then examine equivariance as a framework for consistency, ensuring that model outputs transform predictably in response to input variations. Together, these methods advance the development of vision systems that are not only high-performing but also more secure and robust by design.

Biography: Raymond A. Yeh is an Assistant Professor at Purdue University in the computer science department. His research is at the intersection of machine learning and computer vision. He develops methods for learning effective computer vision models, with a recent focus on model immunization and designing vision models with provable equivariance guarantees. Before joining Purdue, Raymond spent a year as a research assistant professor at the Toyota Technological Institute at Chicago (TTIC). He holds a PhD, an M.S., and B.S. in ECE from the University of Illinois at Urbana-Champaign (UIUC). Raymond is a recipient of the Google Research Scholar, Google PhD Fellowship, the Mavis Future Faculty Fellowship, and the Henry Ford II Scholar Award.

See you soon!