Yifan Feng

Yifan Feng 冯一凡

Department of Analytics and Operations, NUS Business School

Institute of Operations Research and Analytics (IORA)

15 Kent Ridge Dr, BIZ1 8-68, Singapore 119245

Email: yifan.feng[AT]nus[DOT]edu[DOT]sg

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 ML/AI, 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.

Google Scholar

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 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). Management Science 70(12):8988-9013. [Journal] [SSRN] [Data and Codes]

Preliminary version in MSOM Supply Chain SIG '22

4. Optimal partition for multi-type queueing systems (with S. Cao, S. He, and Z. Wang). Forthcoming in Mathematics of Operations Research. [Journal] [Arxiv]

Working Papers

1. Revisiting gig labor supply curves: evidence from a logistics platform (with S. Hu and J. Keppo). [SSRN] (New)

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

Preliminary version in NeurIPS '22 [Link]
Featured in EC '25 Workshop on New Directions in Social Choice (Spotlight)
Third prize, CSAMSE best paper award competition 2023
Finalist, POMS-HK Best Student Paper Award Competition 2025 (Entrant: Yuxuan Tang)

3. Learning to select and rank from choice-based feedback: a simple nested approach (with J. Yang). [Arxiv] (New)

Preliminary version in ICML '23 [Link]

4. A behavioral model for exploration vs. exploitation: theoretical framework and experimental evidence (with J. Ding and Y. Rong). [Arxiv] (New)

Preliminary version in EC '25

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

Preliminary version in EC '24
Preliminary version in MSOM Service SIG '23

6. Disconnectedness brings robustness? On network design for matching with vertex interdiction (with E. Ang). [SSRN]

Teaching

Quantitative Risk Management (MS Bus. Analytics): 2020 - present
Analytics for Risk Management (BBA spec. Bus. Analytics): 2021 - present

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