About Me 

I am an Assistant Professor in the Department of Analytics and Operations (DAO) at NUS Business School. I am also affiliated with the Institute of Operations Research and Analytics (IORA) and the Artificial Intelligence Institute at NUS. 

I integrate tools from data science, economics, and optimization to tackle complex challenges in platforms and markets. My primary focus is on learning, experimentation, and information acquisition. I also work on problems for demand fulfillment. 

CV: [Link]

Google Scholar: [Link]

Publication 

1. Robust learning of consumer preferences (with R. Caldentey and C.T. Ryan). Operations Research 70(2):918-962. [Journal] [SSRN]

2. Dynamic learning and market making in spread betting markets with informed bettors (with J. R. Birge, N. B. Keskin and A. Schultz). Operations Research 69(6):1746-1766. [Journal] [SSRN]

• • Preliminary version in the Proceedings of the 2019 ACM Conference on Economics and Computation (EC '19)

  • Featured in Chicago Booth Review [Link]

3. Designing sparse graphs for stochastic matching with an application to middle-mile transportation management (with R. Caldentey, L. Xin, Y. Zhong, B. Wang, and H. Hu). Forthcoming in Management Science [Journal] [SSRN] [Data and Codes]

• Preliminary version selected for MSOM Supply Chain SIG 2022 conference

Working Papers

1. Learning to rank under strategic "brush wars" (with Q. Li and H. Chen).  [SSRN] (New)

• Preliminary version accepted in 2024 ACM Conference on Economics and Computation (EC '24)

• Preliminary version selected for MSOM Service SIG 2023 conference

2. A Mallows-type model for preference learning from (ranked) choices (with Y. Tang). [SSRN] 

• Preliminary version in Advances in Neural Information Processing Systems 35 (NeurIPS '22) [Link]

• Third prize, CSAMSE (Chinese Scholars Association for Management Science and Engineering) best paper award competition 2023 [link]

3. Nested Elimination: A simple algorithm for best-item identification from choice-based feedback (with J. Yang). [Arxiv]

• Preliminary version in Proceedings of the 40th International Conference on Machine Learning (ICML '23) [Link]  

4. Myopic Quantal Response Policy: Thompson sampling meets behavioral economics  (with J. Ding and Y. Rong). [Arxiv]

5. Optimal partition for multi-type queueing systems (with S. Cao, S. He, and Z. Wang). [Arxiv]

Teaching

• Quantitative Risk Management (MS Bus. Analytics): 2020-present

• Analytics for Risk Management (BBA spec. Bus. Analytics): 2021-present