Jackie Baek

I am an assistant professor at NYU Stern in the Department of Technology, Operations and Statistics. Prior to this, I was a research fellow in the Simons Institute at UC Berkeley, and I obtained my PhD in Operations Research from MIT, advised by Prof. Vivek Farias.

My research focuses on data-driven algorithms that learn from and interact with humans. I study the societal impact of algorithmic systems, design practical algorithms for socio-technical applications, and develop methods for effective human-AI collaboration.

Email: baek (at) stern (dot) nyu (dot) edu
Office: Kaufman Management Center, 8-77
CV

Research

Working Papers

• Personalized Promotions in Practice: Dynamic Allocation and Reference Effects
  with Will Ma, Dmitry Mitrofanov
• Hiring under Congestion and Algorithmic Monoculture: Value of Strategic Behavior
  with Hamsa Bastani, Shihan Chen
• Social Learning with Limited Attention: Negative Reviews Persist under Newest First
  with Atanas Dinev, Thodoris Lykouris
  Major Revision, Operations Research
  • Appeared in the 25th ACM Conference on Economics and Computation (EC), 2024
  • Second place, Junior Faculty Interest Group (JFIG) Paper Competition 2025
• The Feedback Loop of Statistical Discrimination (link to talk)
  with Ali Makhdoumi
  Major Revision, Management Science
  • Appearing in the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2025
• Leveraging Reusability: Improved Competitive Ratio of Greedy for Reusable Resources
  with Shixin Wang

Publications

• When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations
  with David Liu, Tina Eliassi-Rad
  ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2025
• Policy Optimization for Personalized Interventions in Behavioral Health
  with Justin Boutilier, Vivek Farias, Jónas Oddur Jónasson, Erez Yoeli
  Manufacturing and Service Operations Management, 2025
  • Winner, Pierskalla Best Paper Award 2024
• The Limits to Learning a Diffusion Model
  with Vivek Farias, Andreea Georgescu, Retsef Levi, Tianyi Peng, Deeksha Sinha, Joshua Wilde, Andrew Zheng
  Management Science, 2025
  • Appeared in the 22nd ACM Conference on Economics and Computation (EC), 2021
• Fair Exploration via Axiomatic Bargaining (link to talk)
  with Vivek Farias
  Management Science, 2024
  • Appeared in NeurIPS 2021 (Spotlight)
  • Second place, MSOM Student Paper Competition 2022
  • Finalist, George Nicholson Student Paper Competition 2021
  • Finalist, RMP Jeff McGill Student Paper Award 2021
  • Honorable Mention, MIT ORC Best Student Paper Award 2021
  • Oral presentation, 1st ACM Conference on Equity & Access in Algorithms, Mechanisms, & Optimization (EAAMO), 2021
• Bifurcating Constraints to Improve Approximation Ratios for Network Revenue Management with Reusable Resources
  with Will Ma
  Operations Research, 2022
  • Appeared in the 12th International Symposium on Algorithmic Game Theory (SAGT), 2019
• TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
  with Vivek Farias
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
• Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
  with COVID-19 Forecast Hub
  Proceedings of the National Academy of Sciences (PNAS), 2022
  • This paper resulted from contributing COVID-19 forecasts (from the paper “The Limits to Learning a Diffusion Model”) to the COVID-19 Forecast Hub.
• A Game-Theoretic Analysis of Reallocation Mechanisms for Airport Landing Slots
  with Hamsa Balakrishnan
  IEEE Transactions on Intelligent Transportation Systems, 2020