Jingyi Gao

Jingyi is a fifth-year PhD student in computer science at the University of Wisconsin-Madison. Her research focuses on learning theory, particularly the design of statistically efficient algorithms that remain reliable under data corruption, missingness, and reproducibility constraints.

Before joining UW-Madison, she earned bachelor’s degrees in mathematics and computer science from the University of Michigan-Ann Arbor.