Ruiting Liang

Hi! I am a postdoctoral researcher, co-advised by Morgane Austern at Harvard Statistics and Jing Lei at CMU Statistics & Data Science. I received my PhD in Computational and Applied Mathematics at the University of Chicago in 2026, where I was very fortunate to be advised by Rina Foygel Barber. Prior to that, I completed my B.S. in Mathematics at the University of Chinese Academy of Sciences in 2021.

I work on the theory of statistical problems in machine learning, with the goal of understanding uncertainty across diverse settings under minimal and actionable assumptions, and how structural information shapes the limits of learning. My research interests include distribution-free inference, algorithmic stability, ranking and model selection, and efficient data deployment.

I also collaborate with astrophysicists on hypothesis testing problems arising in astronomical data analysis, with the support from the NSF–Simons AI Institute for the Sky (SkAI institute).

Email · LinkedIn · GitHub

Papers

• Rolling conformal prediction in sequential model training
  Chen Cheng*, Ruiting Liang*, and Rina Foygel Barber. arXiv:2609.26951

• False positive control in time series coincidence detection
  Ruiting Liang, Samuel Dyson, Rina Foygel Barber, and Daniel E. Holz. arXiv:2512.17372

• Assumption-free stability for ranking problems
  Ruiting Liang, Jake A. Soloff, Rina Foygel Barber, and Rebecca Willett. arXiv:2506.02257

• Conformal prediction after data-dependent model selection
  Ruiting Liang, Wanrong Zhu, and Rina Foygel Barber. Journal of the American Statistical Association (to appear). arXiv:2408.07066

• Algorithmic stability implies training-conditional coverage for distribution-free prediction methods
  Ruiting Liang and Rina Foygel Barber. Annals of Statistics 53(4):1457-1482. arXiv:2311.04295

Teaching

As a Teaching Assistant at the University of Chicago:

• STAT/CAAM 30900 Mathematical Computation I: Matrix Computation Course, Autumn 2022
• STAT/CAAM 31210 Applied Functional Analysis, Winter 2023-2025
• STAT/CAAM 31220 Partial Differential Equations, Spring 2023-2024
• STAT/CAAM 31430 Applied Linear Algebra, Autumn 2023

My teaching has been recognized with a 2023 CAM Outstanding TA Award.

Miscellaneous

Beyond research, a few personal notes can be found here.