Angela Zhou


401S Bridge Hall

I am an Assistant Professor at USC Marshall Data Sciences and Operations, in the Operations group.

Previously I was a research fellow at the Simons program on causality, a FODSI postdoc at UC Berkeley, hosted by Bin Yu, and Michael I. Jordan. I obtained my PhD from Cornell University in Operations Research and Information Engineering working with Nathan Kallus at Cornell Tech. My work was previously supported on a NDSEG fellowship.

My research interests are broadly in data-driven decision making under uncertainty, including operations, statistical machine learning, and causal inference, and the interplay of statistics and optimization.

Email: zhoua at

[Scholar], [CV],

Research interests by topic:

selected publications

  1. Data-Driven Influence Functions for Causal Inference and Optimization-Based Estimators
    Michael Jordan, Yixin Wang, and Angela Zhou
    Supersedes Empirical Gateaux Derivatives for Causal Inference (oral at Neurips 2022)
  2. Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders
    David Bruns-Smith, and Angela Zhou
  3. Optimizing and Learning Sequential Assortment Decisions with Platform Disengagement
    Mika Sumida, and Angela Zhou
  4. Minimax-Optimal Policy Learning under Unobserved Confounding
    Nathan Kallus, and Angela Zhou
    Management Science (2021), supersedes Neurips 2018 version 2023
  5. Assessing algorithmic fairness with unobserved protected class using data combination
    Nathan Kallus, Xiaojie Mao, and Angela Zhou
    Management Science (2020). A preliminary version appeared at FaCCT 2020 2023


Sep 21, 2023 Delighted to share that my paper on Optimal and Fair Encouragement Policy Evaluation and Learning is accepted at Neurips 2023! TL;DR: under incomplete take-up, we care both about utility and who gets access to services. Let’s work together to equitably reduce administrative burdens. See you in New Orleans!
Sep 21, 2023 Big update to Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders, with new and exciting results on complex healthcare data and warm-starting RL!
Aug 30, 2023 Check out our report on EAAMO 2022 in SIGecom Exchanges!
Aug 23, 2023 I’ll be an Area Chair for AISTATS 2023.
Aug 10, 2023 New paper posted on Optimizing and Learning Assortment Decisions in the Presence of Platform Disengagement! (with Mika Sumida)
Jul 1, 2023 Our paper on An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls was accepted at the journal of Statistics and Public Policy!
Jun 1, 2023 Major (working) update on Data-Driven Influence Functions for Causal Inference and Optimization-Based Estimators, with new results on sensitivity analysis!
Apr 13, 2023 Upcoming talks at USC ShowCAIS (April), USC Econometrics Reading group (April), Simons (Causality reunion) (May), Socal OR/OM Day (May), Stanford OIT (June), MSOM
Feb 1, 2023 New paper on Robust Fitted-Q-Iteration under Unobserved Confounders!
Jan 15, 2023 Serving as a Tutorials Chair and an Area-Chair for FAccT 2023, Scientific Integrity Chair for UAI 2023.