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I am a fourth-year PhD student in Operations Management at Booth School of Business, University of Chicago.
I am fortunate to be co-advised by Prof. Linwei Xin
and Prof. Will Ma.
Previously, I received a B.S. in Applied Mathematics from Zhejiang University. My research lies at the intersection of decision-making under uncertainty, data-driven optimization, and AI.
I develop and analyze algorithms for large-scale operations problems,
with applications in supply chain management, resource allocation, and deployable deep reinforcement learning systems.
I am excited to explore how an operations perspective can illuminate the behavior and success of modern AI methods
and how they can be tailored to specific operations problems to sharpen decision-making. Email: yaqi.xie@chicagobooth.edu |
Horizon-Free Fast Rates for Inventory Learning
Yaqi Xie, Will Ma, Linwei Xin
DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management
[Slides]
Yaqi Xie, Xinru Hao, Jiaxi Liu, Will Ma, Linwei Xin, Lei Cao, Yidong Zhang
Forthcoming in INFORMS Journal on Applied Analytics, 2026
Finalist for the INFORMS 2025 Daniel H. Wagner Prize
Covered in Alibaba Taobao & Tmall Press Release and Columbia Business Insights, 2026
4-page preliminary version appeared at NeurIPS 2025 MLxOR Workshop
VC Theory for Inventory Policies
[Slides]
Yaqi Xie, Will Ma, Linwei Xin
Major Revision in Management Science
Finalist for the INFORMS 2025 APS Best Student Paper Prize
Selected for presentation in the MSOM 2024 Supply Chain Management SIG
The Benefits of Delay to Online Decision-Making
[Slides]
Yaqi Xie, Will Ma, Linwei Xin
Management Science, 2025
Selected for presentation in the MSOM 2023 Supply Chain Management SIG
Covered in Chicago Booth Review, 2023
Dynamic Seat Selection Surcharge and Allocation Policy in Selling High-Speed Train Tickets
Yaqi Xie, Zizhuo Wang
Production and Operations Management, 2025
Booth School of Business, Teaching Assistant:
Operations Management (MBA), Winter 2025
Supply Chain Management (Undergraduate), Winter 2025
Linear Programming (PhD), Fall 2023