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 design polynomial-time algorithms for decision-making in combinatorial and strategic settings. My research bridges Combinatorial Optimization, Algorithmic Game Theory, and Reinforcement Learning to develop approximation frameworks with provable performance guarantees for constrained, uncertain, and robust multi-agent sequential decision problems.

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