Scholar
Puheng Li
Google Scholar ID: keEBSDUAAAAJ
Statistics PhD Student, Stanford University
Citations & Impact
Citations
72
H-index
3
i10-index
2
Publications
5
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- - Publications: CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers (ICCV 2025)
- - Publications: Analyzing the Role of Permutation Invariance in Linear Mode Connectivity (AISTATS 2025)
- - Publications: On the Generalization Properties of Diffusion Models (NeurIPS 2023)
- - Publications: FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee (ICLR 2023)
- - Publications: Exploring Neural Network Landscapes: Star-Shaped and Geodesic Connectivity (arXiv, Apr. 2024)
- - Awards: 2023 Stars of Tomorrow, Microsoft Research Asia
- - Awards: 2023 Excellent Graduate (PKU & Beijing)
- - Awards: 2022 Leo Koguan Scholarship
- - Awards: 2022, 2021, 2020 Merit Student of Peking University
- - Awards: 2021 Peking University Talent Pool Scholarship
- - Awards: 2020 Yizheng Alumni Scholarship
- - Awards: 2018 Gold Medal at the 34th Chinese Mathematical Olympiad (CMO)
- - Awards: 2017 Silver Medal at the 34th Chinese Mathematical Olympiad (CMO)
Research Experience
- - Teaching Assistant, Stanford University (2025-2026 Autumn)
- - Applied Scientist Intern, Amazon (Jun. 2025 - Sep. 2025), worked on LLMs for fraud detection and prevention
- - Research Scientist Intern, Machine Learning Group, Microsoft Research Asia (Mar. 2023 - Jun. 2023), worked on estimating the generalization error of score-based diffusion models under the supervision of Dr. Zhong Li, Dr. Huishuai Zhang, and Dr. Jiang Bian
Education
- - Ph.D. in Statistics, 2023-present, Department of Statistics, Stanford University, Advisors: Prof. Emmanuel Candès and Prof. Renyuan Xu
- - B.S. in Statistics, 2023, School of Mathematical Sciences, Peking University, Advisors: Prof. Lei Wu, Prof. Weijie Su, Prof. Linjun Zhang, and Prof. James Zou
- - High School Diploma (Mathematics), 2019, Shanghai High School
Background
- - Research Interests: Leveraging statistical methods to guide modern machine learning, making them more interpretable, reliable, efficient, and accurate
- - Professional Field: Statistics
- - Introduction: Third-year PhD student in the Department of Statistics at Stanford University, advised by Prof. Emmanuel Candès and Prof. Renyuan Xu
Miscellany
- - Personal Interests: Not specifically mentioned
