About Me

I am an Assistant Professor of Operations Management and Statistics at the Joseph L. Rotman School of Management, University of Toronto, and an affiliated faculty member at the School of Cities. My research broadly explores data-driven decision-making and optimization under uncertainty, with a keen interest in revenue management, sustainable operations, transportation and logistics.

Before joining the University of Toronto, I earned my Ph.D. in Industrial Engineering and Operations Research from the University of California, Berkeley, advised by Max Shen and Aditya Guntuboyina. During my doctoral studies, I gained industry experience as a Research Scientist at Amazon's Supply Chain Optimization Technologies team and Alibaba Cloud. I received my B.S. in Mathematics from USTC.

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News

• 01/2025 Delighted to host Andrea Li (Too Good To Go) for a seminar at Rotman.
• 11/2024 Had a great time attending the Economics of QIT workshop at USC.
• 10/2024 New working paper "Designing Surprise Bags for Surplus Foods" explores optimal strategies for stores in balancing revenue, customer satisfaction, and sustainability in food waste reduction.
• 09/2024 Offering a new Rotman PhD topic course on nonparametric models and methods for data-driven decision-making in Fall 2024.
• 07/2024 I gave a 60-minute talk at Rotman Young Scholar Seminar [Video Recording].
• 06/2024 Presenting in MSOM at Minneapolis, RMP at Los Angeles, and ISMP at Montreal. See you there!
• 05/2024 New version of our Learning While Repositioning paper is posted, where we introduce an asymptotically optimal base-stock repositioning policy and an efficient online algorithm that circumvents the curse of dimensionality arising from network structure.
• 04/2024 I am excited and grateful to receive the NSERC Discovery Grant!
• 02/2024 Congratulations to my student mentee Zeqi Ye for being admitted to the Northwestern IEMS PhD Program!
• 01/2024 Paper on Smoothness Adaptive Dynamic Pricing is accepted to AISTATS 2024.
• 01/2024 Teaching RSM270 Operations Management in Winter 2024.
• 12/2023 Approved funding from the CANSSI Ontario Multidisciplinary Doctoral (Mdoc) Training Program (Joint with Qiang Sun)!
• 12/2023 Talks at USTC School of Management and POMS-HK.
• 10/2023 I will be at INFORMS Annual Meeting 2023 at Phoenix (related sessions).
• 08/2023 Invited talks at MOPTA 2023 ("Potential Energy Advantage of Quantum Economy") and YinzOR 2023 ("Intertemporal Pricing in the Presence of Consumer Behaviors").
• 06/2023 Honored to receive the Second Place in Doctoral Dissertation Award Competition, Conference on SCM in the Post-Pandemic and AI Age. See the recording for a brief 20-min introduction.
• 01/2023 Excited to teach as an instructor for the first time! Welcome to STAT 153: Introduction to Time Series.
• 12/2022 New manuscript "Learning While Repositioning in On-Demand Vehicle Sharing Networks" is posted on SSRN!
• 10/2022 Our paper "Quantum Computing Methods for Supply Chain Management" is published on the Proceeding of 2022 IEEE/ACM 7th Symposium on Edge Computing - Workshop on Quantum Computing!
• 08/2022 I won a prize in the flash talk competition at YinzOR 2022 held by Carnegie Mellon University!

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To Students

I always look forward to working with highly motivated students. Feel free to contact me via email with your resume. Prospective PhD students are encouraged to apply to the Rotman OMS PhD program.