Bio

I am currently a Ph.D. student in the Department of Statistics, University of Wisconsin–Madison. I am fortunate to be advised by Professor Yiqiao Zhong.

Prior to Ph.D., I received my M.S. in Statistics from University of Chicago in 2022, and B.Eng. in Industrial Engineering from Tsinghua University in 2020.

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Interests
  • Foundations of Deep Learning
  • Bias in Large Language Models
  • Applied Statistics
Education

  • Ph.D. in Statistics

    University of Wisconsin–Madison

  • M.S. in Statistics

    The University of Chicago

  • B.Eng. in Industrial Engineering

    Tsinghua University

Honors and Awards

  • ASA SLDS Conference 2026: Student, Post-doc, and Early Career Researcher Paper Awards, American Statistical Association Statistical Learning and Data Science Section, 2026.

  • Honorable Mention: Outstanding Performance as a TA for Graduate Courses, UW-Madison Department of Statistics, 2026. [Link]

  • Frontiers in Statistical Machine Learning (FSML) Travel Award, the Institute of Mathematical Statistics (IMS), 2025. [Link]

  • MMLS 2025 Honorable Mention Poster Award, Midwest Machine Learning Symposium, 2025. [Link]

  • NESS Student Poster Award, New England Statistical Society, 2025. [Link]

Featured Publications
A Statistical Theory of Overfitting for Imbalanced Classification
Refining Covariance Matrix Estimation in Stochastic Gradient Descent through Bias Reduction
Recent Publications
Jingyang Lyu, Kangjie Zhou, Yiqiao Zhong (2026). A Statistical Theory of Overfitting for Imbalanced Classification. The Fourteenth International Conference on Learning Representations.
Cite Code Poster Slides arXiv OpenReview Blog
Ziyang Wei, Wanrong Zhu, Jingyang Lyu, Wei Biao Wu (2026). Refining Covariance Matrix Estimation in Stochastic Gradient Descent through Bias Reduction. The 29th International Conference on Artificial Intelligence and Statistics.
Cite OpenReview
Faan Chen*, Jingyang Lyu*, Tianye Wang, NN Sze (2023). Exploring the association between quantified road safety target attributes and their success: An empirical analysis from OECD countries using panel data. Journal of safety research.
Cite link
Faan Chen, Yilin Zhu, Jiacheng Zu, Jingyang Lyu, Junfeng Yang (2022). Appraising road safety attainment by CRITIC-ELECTRE-FCM: a policymaking support for Southeast Asia. Transport policy.
Cite link
Faan Chen*, Jingyang Lyu*, Tianye Wang (2020). Benchmarking road safety development across OECD countries: an empirical analysis for a decade. Accident Analysis & Prevention.
Cite link
Talks & Events

Invited & Contributed Talk

The 38th New England Statistics Symposium (NESS 2025)Yale2025.06
Math Machine Learning seminar MPI MIS + UCLAUCLA2025.03
Institute for Foundations of Data Science Ideas ForumUW–Madison2024.11

Poster Presentation

The Inaugural Workshop on Frontiers in Statistical Machine Learning (FSML)Vanderbilt2025.08
Midwest Machine Learning Symposium (MMLS 2025)UChicago2025.06
The 38th New England Statistics Symposium (NESS 2025)Yale2025.06
Midwest Optimization & Statistical Learning Conference 2025Northwestern2025.05
6th Annual Data Science Research BazaarUW–Madison2025.03
100th Transportation Research Board (TRB) Annual MeetingVirtual2021.01