Students

Current Doctoral Students:

• Junting Duan, Management Science and Engineering   
  Joint work: Target-PCA: Transfer Learning Large Dimensional Panel Data, Factor Analysis for Causal Inference on Large Non-Stationary Panels with Endogenous Treatment, Imputation-Powered Inference for Missing Covariates
• Greg Zanotti, Management Science and Engineering   
  Joint work: Deep-Learning Statistical Arbitrage, Automatic Outlier Rectification via Optimal Transport, The Microstructure of Cryptocurrency Markets: Men vs. Machine
• Enrica Archetti, Management Science and Engineering
  Joint work: How Much Sustainability is Really in Stock Prices?
• Xueye Ping, Management Science and Engineering
  Joint work: Spanning the Option Price Surface, A Universal Factor Model for Equities and Derivatives
• Aldis Elfarsdottir, Management Science and Engineering
  Joint work: Strategic Environmental Reporting
• Rose Wang, Management Science and Engineering
  Joint work: Bridging the Yield Gap, International Yield Curves
• Alex Yang, Computational and Mathematical Engineering
• Andrew Caosun, Management Science and Engineering
• Adam Rebei, Computational and Mathematical Engineering (co-advised with Kay Giesecke)
• Jason Pan, Management Science and Engineering (co-advised with Kay Giesecke)
• David Dai, Management Science and Engineering

Former Doctoral Students:

• Luyang Chen, Ph.D. 2019, Computational and Mathematical Engineering (co-advised with George Papanicolaou)   
  Thesis: Studies in Stochastic Optimization and Applications   
  Joint work: Deep-Learning in Asset Pricing, Asset Pricing Tests for a Large Number of Assets   
  First position: Quantitative Analyst, Two Sigma, New York
• Ruoxuan Xiong, PhD. 2020, Management Science and Engineering   
  Thesis: Essays on High Dimensional Statistics   
  Joint work: State-Varying Factor Models of Large Dimensions, Interpretable Sparse Proximate Factors for Large Dimensions, Inferential Theory for Partially Observed Factor Models of Large Dimensions   
  First position: Assistant Professor, Emory University
• Xiaocheng Li, Ph.D. 2020, Management Science and Engineering (co-advised with Kay Giesecke)   
  Thesis: Machine Learning for Operations Research   
  Joint work: Machine Learning Estimators for Corporate Default Probabilities   
  First position: Assistant Professor, Imperial College London
• Jason Zhu, Ph.D. 2021, Management Science and Engineering   
  Thesis: Essays in Asset Pricing and Machine Learning   
  Joint work: Deep-Learning in Asset Pricing, The Forest Through the Trees: Decision Trees in Asset Pricing, TextGNN   
  First position: Data Scientist at Microsoft
• Jorge Guijarro-Ordonez, Ph.D. 2021, Mathematics (co-advised with George Papanicolaou)   
  Thesis: Stochastic Control and Deep Learning Approaches to High-Dimensional Statistical Arbitrage   
  Joint work: Deep-Learning Statistical Arbitrage   
  First position: Quantitative Researcher at BlackRock
• Ye Ye, Ph.D. 2022, Management Science and Engineering   
  Thesis: Essays in Machine Learning in Finance   
  Joint work: Stripping the Discount Curve, Shrinking the Term Structure   
  First position: Research Software Engineer at Uber
• Zihan Lin,  Ph.D. 2023, Computational and Mathematical Engineering   
  Thesis: Essays on Machine Learning and Price Impact in Institutional Finance   
  Joint work: Machine-Learning the Skill of Mutual Fund Managers   
  First position: Quantitative Researcher at Hudson River Trading
• Sven Lerner, Ph.D. 2023, Computational and Mathematical Engineering 
  Thesis: Estimating Latent Structure in Financial Data 
  Joint work: Missing Financial Data, Spanning the Option Price Surface 
  First position: Quantitative Analyst at Citadel
• Jiacheng Zou, Ph.D. 2024, Management Science and Engineering   
  Thesis: Inference for Large Panel Data with Machine Learning 
  Joint work: Inference of Large Panel Data with Many Covariates, Large Dimensional Change Point Detection
  First position: Postdoctoral researcher, IEOR Columbia University
• Florian Fiaux, Ph.D. 2024, Economics (co-advised with Monika Piazzesi) 
  Thesis: Essays in Empirical Finance 
  Joint work: Investment Styles and Stock Return Prediction 
  First position: Quantitative Researcher at TerraCotta
• Yang Fan, Ph.D. 2025, Computational and Mathematical Engineering  
  Thesis: Machine Learning and Statistical Perspectives on Financial Market Behavior 
  Joint work: Do Algorithmic Traders Lead to Market Instability? A Multi-Agent Reinforcement Learning Approach, Large Dimensional Change Point Detection 
  First position: Quantitative Researcher at Cubist Systematic Strategies

Ph.D. Committee:

• Moojoong Ra, Management Science and Engineering
• Yexiang Wei, Management Science and Engineering
• Joongyeub Yeo, Computational and Mathematical Engineering
• Carl-Fredrik Arndt, Computational and Mathematical Engineering
• Simon Hilpert, Economics
• Jessie Li, Economics
• Yu An, GSB Finance
• Michael Ohlrogge, Management Science and Engineering
• Kyu Koh Yoo, Energy Resources Engineering
• Wonjin Yun, Energy Resources Engineering
• Markus Zechner, Energy Resources Engineering
• Enguerrand Horel, Computational and Mathematical Engineering
• Amy Wang, GSB Finance
• Nadia Kotova, GSB Finance
• Ziyi Yang, Mechanical Engineering
• Bernardo Ramos, Management Science and Engineering
• Xu Lu, GSB Finance
• Hao Ma, Swiss Finance Institute
• Guanting Chen, Computational and Mathematical Engineering
• Tizian Otto, Finance, University of Hamburg
• Xuhui Zhang, Management Science and Engineering
• Geoff Ramseyer, Computer Science
• Lin Fan, Management Science and Engineering
• Kaper Johansson, Electrical Engineering
• Jason Liang, Computational and Mathematical Engineering