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Qinyi Chen

Ph.D. candidate in Operations Research at MIT

I am a fourth-year PhD student in the Operations Research Center (ORC) at MIT, where I am advised by Prof. Negin Golrezaei. My research centers on designing ML and optimization algorithms tailored for operations of digital marketplaces, including online advertising, recommender systems, revenue and inventory management. My research interests span multi-armed bandits and RL, game and auction theory, data-driven optimization and AI/ML fairness.


Prior to MIT, I received my B.S. in Applied Mathematics with a specialization in computing from UCLA in 2020. In summer of 2023, I interned at eBay Search & Monetization Team as an applied researcher intern.



Interpolating Item and User Fairness in Multi-Sided Recommendations

Q. Chen, J.C.N. Liang, N. Golrezaei, and D. Bouneffouf. 

Under review.

  • Preliminary version accepted at the Symposium on Foundations of Responsible Computing (FORC 2024) 

  • Accepted for presentation at 2024 MSOM Conference, 2024 Revenue Management & Pricing Conference

Fair Assortment Planning

Q. Chen, N. Golrezaei, and F. Susan. 

Under review.

  • Finalist, INFORMS IBM Service Science Best Student Paper Competition (presentation video)

  • Finalist, INFORMS Social Media Analytics Best Student Paper Competition

  • Honorable Mention, INFORMS Minority Issue Forum Student Poster Competition

  • Accepted for presentation at 2022 MSOM Service Management SIG Conference (acceptance rate:12%)

  • Accepted for presentation at 2022 Revenue Management & Pricing Conference, Spotlight Presentation (presentation video)


Optimization-Based Budget Pacing in eBay Sponsored Search

Q. Chen, P.H. Nguyen, D. Gligorijevic.

The Web Conference 2024 (WWW'24), Industry Track

Non-Stationary Bandits with Auto-Regressive Temporal Dependency.

Q. Chen, N. Golrezaei and D. Bouneffouf.

The 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks.

Q. Chen, M.A. Porter​.

Journal of Complex Networks, February 2022.

Subgraph Matching on Multiplex Networks.

J.D. Moorman, T.K. Tu, Q. Chen, X. He, and A.L. Bertozzi.

IEEE Transactions on Network Science and Engineering, February 2021.

Inexact Attributed Subgraph Matching.

T.K. Tu, J.D. Moorman, D. Yang, Q. Chen and A.L. Bertozzi.

2020 IEEE International Conference on Big Data (Big Data)

Filtering Methods for Subgraph Matching on Multiplex Networks.

J.D. Moorman, Q. Chen, T.K. Tu, Z. Boyd, and A.L. Bertozzi.

2018 IEEE International Conference on Big Data (Big Data)

Recent Talks

"Interpolating Item and User Fairness in Multi-Sided Recommendations"
        -  Symposium on Foundation of Responsible Computing (FORC), June 2024
        -  ML Tea Talk, MIT CSAIL, April 2024        
        -  INFORMS Annual Meeting, October 2023 

"Fair Assortment Planning"
-  INFORMS Annual Meeting, October 2023

        -  POMS Annual Meeting, May 2023

        -  INFORMS Annual Meeting, October 2022
        - Data, Learning, and Markets workshop at UIUC, October 2022

        -  Young Researchers Workshop at Cornell University, October 2022 
        -  MSOM Service Management SIG Conference, June 2022
        -  RMP Conference, Spotlight Presentation, June 2022
        -  EC'22 Poster Session, June 2022
        -  Marketplace Innovation Workshop (MIW), May 2022

"Non-Stationary Bandits with Auto-Regressive Temporal Dependency"
        -  NeurIPS, December 2023
INFORMS Annual Meeting, October 2023 
        -  INFORMS Annual Meeting, October 2022

        -  IJCAI-ECAI 2022 Doctoral Consortium, July 2022
        -  MIT-IBM Watson AI Lab Poster Session, April 2022
        -  INFORMS Annual Meeting, October 2021
        -  MIT-IBM Watson AI Lab Poster Session, April 2021

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