Jackie Baek

I am a research fellow in the Simons Institute at UC Berkeley in the Data-Driven Decision Processes program. In January 2023, I will join NYU Stern as an assistant professor in the Department of Technology, Operations and Statistics. I recently obtained a PhD in Operations Research from MIT, advised by Prof. Vivek Farias.

Broadly, my research develops machine learning algorithms for decision making, focusing on efforts to bridge theory to practice. I am interested in studying the societal impact of algorithms (e.g. fairness in algorithmic hiring), as well as designing practical algorithms for impactful applications (e.g. global health).

Email: baek (at) stern (dot) nyu (dot) edu
CV

Research

• Fair Exploration via Axiomatic Bargaining (link to talk)
  with Vivek Farias
  Submitted. Preliminary version: NeurIPS 2021 (Spotlight)
  • 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, 2021
• The Limits to Learning a Diffusion Model
  with Vivek Farias, Andreea Georgescu, Retsef Levi, Tianyi Peng, Deeksha Sinha, Joshua Wilde, Andrew Zheng
  Submitted. Preliminary version: 22nd ACM conference on Economics and Computation (EC), 2021
  • Finalist, Post-Pandemic Supply Chain and Healthcare Management Best Paper
  • Oral Presentation, NeurIPS 2021 Workshop on Causal Inference Challenges in Sequential Decision Making
• Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
  with COVID-19 Forecast Hub
  Forthcoming in PNAS
  • This paper resulted from contributing COVID-19 forecasts (from the paper “The Limits to Learning a Diffusion Model”) to the COVID-19 Forecast Hub.
• TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
  with Vivek Farias
  Submitted
• Bifurcating Constraints to Improve Approximation Ratios for Network Revenue Management with Reusable Resources
  with Will Ma
  Operations Research, 2022 (Articles in Advance)
  • Preliminary version: Proceedings of the 12th International Symposium on Algorithmic Game Theory (SAGT), 2019
• A Game-Theoretic Analysis of Reallocation Mechanisms for Airport Landing Slots
  with Hamsa Balakrishnan
  IEEE Transactions on Intelligent Transportation Systems, 2020

Teaching

• 15.778: Introduction to Operations Management. Summer 2020.
  Teaching Assistant (Instructor: Vivek Farias)
• 15.071: The Analytics Edge. Spring 2018
  Teaching Assistant (Instructor: Robert Freund)
• 15.060: Computing in Optimization and Statistics. January 2017, 2018
  Instructor for a 3-hour lecture, Introduction to Terminal and Git

Talks

• Fair Exploration via Axiomatic Bargaining
  • Cornell ORIE Young Researchers Workshop, 2021
  • Data Science Lab Seminar (MIT), 2021
  • Marketplace Innovation Workshop, 2021
  • MSOM Conference, 2021
  • RMP Conference, 2021
• The Limits to Learning a Diffusion Model
  • Healthcare Operations SIG Meeting, 2021
  • EC, 2021
• TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
  • INFORMS Annual Meeting, 2020
• Bifurcating Constraints to Improve Approximation Ratios for (Reusable) Network Revenue Management
  • INFORMS Annual Meeting, 2019
  • Revenue Management and Pricing, 2019
  • POMS Annual Conference, 2019
• Mechanism Design for Airport Landing Slot Exchange
  • LIDS Student Conference, 2018
    - Runner up, Best Student Presentation
  • INFORMS Annual Meeting, 2017, 2018