About Me

I am a final-year Ph.D. candidate in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley, where I am advised by Zuo-Jun (Max) Shen and Aditya Guntuboyina (Department of Statistics). Prior to joining Berkeley, I received my B.S. degree in Mathematics from the University of Science and Technology of China in 2017.

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Research Interests

I am interested in developing methodologies and algorithms for sequential and data-driven decision-making. I have focused on bridging theory and practice in modeling and analysis, and I leverage an eclectic set of techniques from statistics, optimization, and machine learning to address real-world problems in retailing platforms, on-demand shared mobility systems, and supply chain management.

I explore practical aspects of my research through industry experience. I worked as a research scientist intern in the Supply Chain Optimization Technologies team at Amazon in the summers of 2020 and 2021, where I built and tested demand forecasting models for supporting inventory planning and control. I also interned in the data science decision support team at Alibaba Cloud in the summer of 2019.

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Updates

• Excited to teach as an instructor for the first time! Welcome to STAT 153: Introduction to Time Series.
• New manuscript Learning While Repositioning in On-Demand Vehicle Sharing Networks is posted on SSRN!
• 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!
• I won a prize in the flash talk competition at YinzOR 2022 held by Carnegie Mellon University!