Research & Professional Services

My Citations               Students supervised

Current Research Directions

  • High-dimensional Statistics and Machine Learning Research Agenda
  • Generative AI and Data Science
  • Graphical, Network modeling, Item Ranking
  • Deep Learning, Reinforcement Learning, Transfer Learning
  • Financial Econometrics and Risk Management
  • Bioinformatics and Biostatistics

Research Interests

Professor Fan's research lies in the developments of statistical machine learning theory and methods and their applications in finance, economics, genomics, and health. His primary research focuses on developing and justifying statistical machine learning methods and AI algorithms that are used to solve problems from the frontiers of scientific research and business operations, with a focus on financial asset pricing, risk modeling, and portfolio choices. This is expanded into other disciplines where the statistics discipline is useful, such as genomics, genetics, and biomedical studies. Professor Fan devotes most of his efforts to the search for intuitively appealing, computationally scalable, data-driven, robust statistical machine learning approaches and AI algorithms and illustrates the approaches with real data and simulated examples. He is also very interested in developing foundational statistical theory and providing fundamental insights into sophisticated statistical machine learning methods. These include distributed computation, deep learning, high-dimensional statistical learning, factor modeling, and network modeling. In Finance, his research focuses on portfolio allocation, high-frequency trading, risk management, financial econometrics, and risk modeling and management.

Professor Fan has co-authored four highly-regarded books and a monograph on Local Polynomial Modeling (1996), Nonlinear time series: Parametric and Nonparametric Methods (2002), The Elements of Financial Econometrics,  Statistical Foundations of Data Science (2020), and Spectral Methods for Data Science, and authored or co-authored over 300 articles on finance, economics, statistical machine learning, computational biology, semiparametric and nonparametric modeling, nonlinear time series, survival analysis, longitudinal data analysis, and other aspects of theoretical and methodological statistics. His research is supported by the National Science Foundation, National Institute of Health, and Office of Naval Research.

Editorial Services

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Current Associate Editor

Past Editors

Past Associate Editors

Professional Services