Ye Luo

Associate Professor

Center for AI for Social Science

Education Background
  • 2010–2015: Massachusetts Institute of Technology, Economics, Doctoral Degree (Full-time)
  • 2007–2010: Massachusetts Institute of Technology, Mathematics and Economics, Bachelor’s Degree (Full-time)
  • 2005–2007: Peking University, Mathematics, Bachelor’s Degree Candidate (Full-time)
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Work Experience

  • 2026-Present: Shenzhen Loop Area Institute, Associate Professor
  • 2025–Present: The University of Hong Kong, Director of AI-Agent Lab of CAMO
  • 2025–Present: Shenzhen Chuangzhi Semi-link Technology Co., Ltd., Independent Director
  • 2025–Present: University of Queensland, Honorary Associate Professor
  • 2022–Present: The University of Hong Kong Business School, Director of Institute of Financial Technology at SZRI
  • 2022–Present: The University of Hong Kong Business School, Associate Director of Institute of Digital Economy and Innovations
  • 2021–Present: The University of Hong Kong Business School, Associate Professor
  • 2018–2021: The University of Hong Kong Business School, Assistant Professor
  • 2017–2018: University of Florida Center for Big Learning, Affiliated Faculty
  • 2015–2018: University of Florida Department of Economics, Assistant Professor
Research Fields
High-Dimensional Econometrics, Causal Inference, Machine Learning, Statistical Inference, AI Multi-Agent System, Economic World Model, AI + Finance, Causal Reinforcement Learning, AI+Simulation
Personal Website
https://www.hkubs.hku.hk/people/ye-luo/
Email
yeluo@slai.edu.cn
Biography

Dr. Ye Luo received his Ph.D from the Massachusetts Institute of Technology in 2015. He received his B.S. degree from the Massachusetts Institute of Technology in 2010, majoring in Mathematics and Economics.

Dr. Ye Luo’s main research interests include high dimensional econometrics/statistics, machine learning and its empirical applications in economics and finance. His current work is focusing on causal machine learning and economic world models.

Dr. Ye Luo has research papers published/forthcoming at Econometrica, Journal of the Royal Statistical Society: Series B, American Economic Review, P&P, etc. Beyond Dr. Ye Luo’s academic research, he has a strong interest in connecting research in data science to the industry. He has given/been invited to give lectures at DiDi, ShunFeng Express, Novartis, etc.

Academic Publications

Academic Achievements：

  1. Luo Y, Ponomarev K, Wang H. Selecting Inequalities for Sharp Identification in Models with Set-Valued Predictions. Review of Economic Studies, 2025 (Top Economics Journal, SCI Q1)
  2. Luo Y, Kueck J, Spindler M. High-Dimensional L2Boosting: Rate of Convergence. Journal of Machine Learning Research, 2025 (SCI Q1)
  3. Luo Y, Kueck J, Spindler M, Wang Z. Estimation and Inference of Treatment Effects with L2-Boosting in High-Dimensional Settings. Journal of Econometrics, 2023 (Top Economics Journal, SCI Q1)
  4. Luo Y, Chen X, Chernozhukov V, Fernandez-Val I, Kostyshak S. Shape-Enforcing Operators for Generic Point and Interval Estimators of Functions. Journal of Machine Learning Research, 2021 (SCI Q1)
  5. Luo Y, Hausman J, Liu H, Palmer C. EIV on LHS Variable in Quantile Regression. Econometrica, 2021 (Top Economics Journal, SCI Q1)
  6. Luo Y, Chernozhukov V, Fernandez-Val I. The Sorted Effect: Discovering Heterogeneous Effect Beyond Their Averages. Econometrica, 2018 (Top Economics Journal, SCI Q1)
  7. Luo Y, Liang F, Jia B, Xue J, Li Q. An Imputation-Consistency Algorithm for High-Dimensional Missing Data Problems and Beyond. Journal of Royal Statistical Society Series B, 2018 (Top Statistics Journal, SCI Q1)

 

Research Awards：

  1. 2010-2012: MIT Economics Department Fellowship, Massachusetts Institute of Technology
  2. 2005-2007: Mingde Fellowship, Peking University
  3. 2005: Gold Medal & 1st Rank with Perfect Score, 45th International Mathematical Olympiad
  4. 2004: Gold Medal & 1st Rank with Perfect Score, 20th Chinese Mathematical Olympiad

 

Research Projects：

Hosted Projects：

  1. 2023-2025: Causal Reinforcement Learning in Dynamic Games, SZRI Research Grant, Principal Investigator (PI), Total Grant 3,000,000 RMB
  2. 2022-2024: Dynamic Learning Mechanism Design, RGC-NSFC Joint Grant, Principal Investigator (PI), Total Grant 1,200,000 HKD + 1,000,000 RMB
  3. 2021-2023: Statistical Inference on High Dimensional Linear Programming, Research Grants Council (RGC) Hong Kong, Principal Investigator (PI), Total Grant 480,000 HKD
  4. 2017-2018: Dynamic Pricing Models via Deep Learning, Didi Chuxing, Principal Investigator (PI), Total Grant 100,000 RMB

Participated Projects ：

  1. 2024-2026: Enhancing Hong Kong’s Role in Sustainable Supply Chain Finance via Technology Transformation, Theme-Based Research Scheme (TRS) Hong Kong, Project No. T32-615/24, Co-Principal Investigator (Co-PI), 1,500,000 HKD entitled
  2. 2020-2023: Financial Technology, Stability and Inclusion, Theme-Based Research Scheme (TRS) Hong Kong, Co-Principal Investigator (Data Science), 3,000,000 HKD entitled