Luofeng Liao

Department of Industrial Engineering and Operations Research, Columbia University

2021 @ Columbia

Hi! My name is Luofeng Liao (廖烙锋 in Chinese) and I am a third-year phd student in the IEOR Department at Columbia.

My research interests are machine learning methods for causal inference and econometrics, learning and inference in market design, and adversarial optimization.

Currently, I’m working with Prof. Christian Kroer on statistical inference theory for equilibrium in auction markets, a theory that is useful for internet advertising business. Prior to Columbia, I received my bachelor’s degree in computer science in Fudan University in China and a master’s degree in statistics in University of Chicago. In UChicago, I used to work with Prof. Mladen Kolar and Prof. Zhaoran Wang. In Fudan I was advised by Prof. Ke Wei.


  1. preprint
    Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis
    Luofeng Liao, Christian Kroer, Sergei Leonenkov, Okke Schrijvers, Liang Shi, Nicolas Stier-Moses, and Congshan Zhang
  2. ICML2024
    Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
    Luofeng Liao, and Christian Kroer
  3. AAAI2024
    Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees
    Zongjun Yang, Luofeng Liao, and Christian Kroer
  4. ICML2023
    Statistical Inference and A/B Testing for First-Price Pacing Equilibria
    Luofeng Liao, and Christian Kroer
  5. ICLR2023
    Statistical Inference for Fisher Market Equilibrium
    Luofeng Liao, Yuan Gao, and Christian Kroer
  6. NeurIPS2022
    Nonstationary Dual Averaging and Online Fair Allocation
    Luofeng Liao, Yuan Gao, and Christian Kroer
  7. Mach. Learn.
    Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax Problems
    Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, and Dacheng Tao
    Maching Learning - Springer 2022
  8. JMLR
    Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning
    Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Mladen Kolar, and Zhaoran Wang
    Journal of Machine Learning Research (forthcoming) 2024
  9. NeurIPS2020
    Provably efficient neural estimation of structural equation model: An adversarial approach
    Luofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Zhaoran Wang, and Mladen Kolar