معرفی
Yunzong Xu is an Assistant Professor in the Department of Industrial and Enterprise Systems Engineering (ISE) and Coordinated Science Laboratory (CSL) at the University of Illinois at Urbana-Champaign, with affiliations in the Departments of Computer Science (CS) and Electrical and Computer Engineering (ECE). He holds a Ph.D. in Data, Systems, and Society from MIT (2023) and dual B.S. degrees from Tsinghua University in Economics and Mathematical Sciences (2018).
His research focuses on machine learning theory, foundations of AI, operations research, and management science, with specific interests in online learning, deep learning, sequential decision making, and mathematical problems related to markets, incentives, and social good. His work bridges theoretical analysis with applications in dynamic pricing, reinforcement learning, and network revenue management.
Recent publications highlight algorithmic complexity in contextual bandits, offline reinforcement learning, and phase transitions in constrained bandit problems. His research has been recognized by awards from INFORMS, Applied Probability Society, and IBM Service Science.
- Honorable Mention, INFORMS George Nicholson Student Paper Competition (2020)
- Winner, INFORMS Data Mining Best Theoretical Paper Award (2020)
- Finalist, Applied Probability Society Best Student Paper Award (2019)
- Finalist, INFORMS Undergraduate Operations Research Prize (2018)
- Finalist, IBM Service Science Best Student Paper Award (2021)
He teaches graduate courses on Foundations of Modern Machine Learning (IE598) and undergraduate courses in optimization models (IE310). For more information, visit his personal homepage.
