Pengrun Huang (黄鹏润)
I am Pengrun Huang, a third-year Ph.D. student in the Computer Science and Engineering Department at the University of California, San Diego. I am fortunate to be co-advised by Kamalika Chaudhuri and Yu-Xiang Wang. Previously, I earned my bachelor’s and master’s degrees in Honors Mathematics from University of Michigan. I was mentored by Maggie Makar.
I work on trustworthy ML, data privacy and confidentiality, with a current emphasis on large language models (LLMs). In particular, I am interested in:
- Identifying training data privacy and confidentiality risk.
- Measuring model memorization.
- Designing defense strategy for privacy attacks.
Selected Publications
Can We Infer Confidential Properties of Training Data from LLMs?
NeurIPS 2025 (Spotlight 3%)
Conditional differential measurement error: partial identifiability and estimation
NeurIPS workshop CML4Impact 2022
