MIT Sloan researchers develop first-of-their-kind algorithms
Researchers at MIT Sloan have created two new algorithms to help balance fairness of item display and user preferences in online marketplaces.
Faculty
Negin Golrezaei is the W. Maurice Young (1961) Career Development Associate Professor of Management and an Associate Professor of Operations Management at the MIT Sloan School of Management.
Her current research interests are in the area of machine learning, statistical learning theory, mechanism design, and optimization algorithms with applications to revenue management, pricing, and online markets. Before joining MIT, Negin spent a year as a postdoctoral researcher at Google Research in New York where she worked with the Market Algorithm team to develop, design, and test new mechanisms and algorithms for online marketplaces.
Negin is the recipient of a 2018 Google Faculty Research Award; 2017 George B. Dantzig Dissertation Award; 2017 INFORMS Revenue Management and Pricing Section Dissertation Prize; 2018 Elwood S. Buffa Doctoral Dissertation Award from the Decision Sciences Institute; University of Southern California (USC) Ph.D. Achievement Award (2017); USC CAMS Graduate Student Prize, for excellence in research with a substantial mathematical component (2017); Honorable mention in the 2016 MSOM Student Paper Competition; and USC Provost's Ph.D. Fellowship (2011).
Negin received her BSc (2007) and MSc (2009) degrees in electrical engineering from the Sharif University of Technology, Iran, and a PhD (2017) in operations research from USC.
Golrezaei, Negin and Evan Yao. Forthcoming. arXiv Preprint.
Galgana, Rigel, and Negin Golrezaei. Manufacturing & Service Operations Management Vol. 27, No. 1 (2025): 200-229. Supplemental Material. arXiv Preprint.
Qinyi Chen, Jason Cheuk Nam Liang, Negin Golrezaei, and Djallel Bouneffouf. In Proceedings of 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC: December 2024. Supplemental Material.
Van Parys, Bart P.G., and Negin Golrezaei. Management Science Vol. 70, No. 6 (2024): 3951-3998. arXiv Preprint .
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, and Vahab Mirrokni. In WWW '24: Proceedings of the ACM on Web Conference, Singapore: May 2024. DSpace.
Golrezaei, Negin, Rad Niazadeh, Kumar Kshitij Patel, and Fransisca Susan, MIT Sloan Working Paper 7065-24. Cambridge, MA: MIT Sloan School of Management, May 2024. SSRN.
Researchers at MIT Sloan have created two new algorithms to help balance fairness of item display and user preferences in online marketplaces.
MIT Sloan students have the opportunity to study generative AI management, analytics for digital platforms, and global energy economies in 2024 – 2025.
When asked how she knew she wanted to be a business school professor, Negin (Nikki) Golrezaei said: "I was drawn to the opportunity to conduct rigorous research on practical and impactful problems in digital platforms. The ability to study these systems analytically and share that knowledge with the next generation through teaching made this career feel like a perfect fit."
"Our work introduces data-driven algorithms that empower fair, efficient bidding across diverse industries."
“...a lot of people are talking about using data to make decisions...an often- overlooked aspect of data is that it can't always be trusted."
Prof. Negin Golrezaei developed a search model that learns consumer preferences to optimize product rankings.