Xiang Li
I am currently a postdoctoral researcher at the University of Pennsylvania, working with Weijie J. Su and Qi Long. I received my B.S. and Ph.D. in Statistics from Peking University, where I was advised by Zhihua Zhang. I will join the Department of Statistics at Rutgers University as an Assistant Professor in January 2027.
My research lies at the intersection of statistics, optimization, and machine learning. I develop statistical and algorithmic foundations for reliable AI, with current work on statistical watermarking for tracing and verifying AI-generated content and on methods for evaluating what large language models know. I also study statistical inference for learning algorithms, federated learning, and online decision-making.
- Aug. 2026 — I will attend the 2026 IMS New Researchers Conference and present Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know? at JSM 2026. Looking forward to connecting!
- Jul. 2026 — Selective Disclosure Watermarking for Large Language Models was accepted to ICML 2026. arXiv
- Mar. 2026 — I will present Optimal Detection for Language Watermarks with Pseudorandom Collisions at ENAR, IWSM, and ICSA.
- Nov. 2025 — I gave an SDLS webinar on LLM API usage and watermarking. Slides
- Sep. 2025 — Two papers were accepted to NeurIPS 2025 as spotlights: one on watermark detection and one on privacy in decentralized federated learning.
- Aug. 2025 — I presented recent work on estimating watermark proportions at JSM 2025.
- Jun. 2025 — At ICSA 2025, I presented work on robust watermark detection and taught a short course on LLM watermarking. Slides
- Apr. 2025 — I received the IMS New Researcher Travel Award.
- Aug. 2024 — I chaired a federated learning session at MOPTA 2024.
- May 2024 — I presented recent watermarking work at the IMS-NUS workshop.