Jeremy McMahan

Hi! I am a Computer Science PhD graduate from the University of Wisconsin-Madison, where I was advised by Jerry Zhu and worked closely with Qiaomin Xie and Yudong Chen.

I study the tractability of sequential decision-making in combinatorial and strategic settings under uncertainty. My research develops polynomial-time approximation and learning algorithms with formal guarantees, and explores how learning can be integrated with classical optimization while preserving provable performance.

My work has applications to routing, resource allocation, digital marketplaces, and safety-critical autonomous systems. I am also interested in improving the combinatorial and strategic reasoning capabilities of AI agents.