- Multiple publications in top-tier conferences such as NeurIPS, COLT, and AISTATS
- Research topics include adversarial robustness, out-of-distribution generalization, and online classification
Research Experience
- Assistant Professor in the Department of Statistics and Data Science at Yale
- Postdoctoral researcher at UC Berkeley as part of FODSI-Simons (one year)
- During his Ph.D., he primarily focused on questions related to learning machine learning models robust against adversarial examples through the lens of learning theory
Education
- Ph.D. from Toyota Technological Institute at Chicago, advised by Nathan Srebro
- Combined BS/MS in Computer Science and Engineering from Penn State, worked with Daniel Kifer and Sean Hallgren
Background
Research interests include the theory and foundations of machine learning, with a particular focus on robustness to adversarial examples and distribution shifts.