Hello! I am a Ph.D. candidate in the Department of IEMS at Northwestern University, and I’m fortunate to be advised by Prof. Sean Sinclair. I received my B.S. in Statistics from the University of Science and Technology of China and my M.S. in Industrial and Operations Engineering from the University of Michigan. Before doing my PhD, I spent four years at Alibaba Cloud as a data scientist, working on learning and optimization methods for large-scale supply chain systems and operations management.
My research lies at the intersection of learning theory and operations research. I am particularly interested in how principles from statistical and online learning can be leveraged to address real-world decision-making problems in operations and supply chains. I personally believe that learning in structured real-world systems can often be simpler than general learning theory suggests, and that operations research applications offer a unique perspective to understand this connection.
Please feel free to reach out if you share similar interests in learning and operations!
Contact: zhongjun [at] u.northwestern.edu
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News
- Sep 2026: Our paper “Offline-Online Reinforcement Learning for Linear Mixture MDPs” was accepted to NeurIPS 2026!
- Apr 2026: New preprint of our paper “Offline-Online Reinforcement Learning for Linear Mixture MDPs” is now available on arXiv. [arXiv]
- Sept 2025: Our paper “Reinforcement Learning in MDPs with Information-Ordered Policies” was selected as a 2025 INFORMS Nicholson Finalist!
- Aug 2025: New preprint of our paper “Reinforcement Learning in MDPs with Information-Ordered Policies” is now available on arXiv. [arXiv]