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Qinyi Chen

Ph.D. candidate in Operations Research at MIT
Email: qinyic@mit.edu

I am a fourth-year PhD student in the Operations Research Center (ORC) at MIT, where I am advised by Prof. Negin Golrezaei. 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 as an applied researcher intern.

 

My research centers around designing online learning and optimization algorithms for online platforms and marketplaces, with applications in online recommendation, assortment optimization, and ads bidding/pricing. Fascinated by the multi-sided dynamics between the platform and its various participants, I hope to design algorithmic approaches that help foster a more fair and efficient online ecosystem.

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Publications & Preprints

Interpolating Item and User Fairness in Multi-Sided Recommendations. 

With N. Golrezaei, J.C.N. Liang and D. Bouneffouf. 

Submitted.

Fair Assortment Planning. 

With N. Golrezaei, and F. Susan. 

Under review at Management Science.

  • 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)

Non-Stationary Bandits with Auto-Regressive Temporal Dependency.

With N. Golrezaei and D. Bouneffouf, in partnership with IBM Research.

Accepted by NeurIPS 2023.​

Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks.

With M.A. Porter​.

Journal of Complex Networks, February 2022.

Subgraph Matching on Multiplex Networks.

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

IEEE Transactions on Network Science and Engineering, February 2021.​

Recent Talks

"Interpolating Item and User Fairness in Multi-Sided Recommendations"
        -  INFORMS Annual Meeting, October 2023 

"Fair Assortment Planning"
        -  INFORMS Annual Meeting, October 2023
        -  POMS Annual Meeting, May 2023
        -  INFORMS Annual Meeting, October 2022
        -  C3.ai 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"
        -  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

Education

September 2020 - May 2025 (Expected)

Massachusetts Institute of Technology

  • Candidate for Ph.D. in Operations Research; GPA: 5.0/5.0

  • Advisor: Prof. Negin Golrezaei

September 2016 - March 2020

University of California, Los Angeles

  • B.S. in Applied Mathematics, Specialization in Computing; GPA: 3.99/4.00

  • Advisor(s): Prof. Andrea Bertozzi, Prof. Mason Porter

  • Summa Cum Laude, College Honors, Departmental Honors

  • 2019-2020 Recipient of Daus Scholarship in Mathematics 

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