Xin Xia

Ph.D. student, Industrial and Systems Engineering, University of Wisconsin-Madison. Advisor: Prof. Kaibo Liu.

My research combines multi-agent reinforcement learning with statistical process control. Where a mobile sensor goes decides what is observed, so I design learning-based sampling and dispatch policies that let fleets of agents, such as unmanned aerial vehicles, detect anomalies quickly in large systems while keeping false alarms under control, with guarantees on coverage, focusing, and detection delay.

Before Madison, I was a research assistant in the Industrial Statistics and Data Analytics Lab at Tsinghua University, advised by Prof. Chen Zhang, working on deep reinforcement learning for bilevel optimization in supply chain and manufacturing systems. I hold an M.Sc. in Electrical and Computer Engineering from Georgia Tech and a B.Eng. in Electrical Engineering and Automation from Tianjin University.

Interests: multi-agent reinforcement learning, sequential change detection, adaptive sampling and dispatch, statistical process control, unmanned aerial vehicles, bilevel optimization, resilient supply chains, language models for text mining.

EmailCVGoogle ScholarGitHub