Linjun Zhang

Linjun Zhang is an Associate Professor in the Department of Statistics at Rutgers University, with a focus on ethical statistical learning, algorithmic fairness, and privacy-preserving techniques. He earned his Ph.D. in Statistics from the University of Pennsylvania (2019) and B.S. from University of Science and Technology of China (2014).

His research bridges theoretical computer science and statistics, addressing challenges in AI safety, differential privacy, and representation learning. Key contributions include frameworks for fair classification, robustness in vision-language models, and multicalibration methods. His work is supported by an NSF CAREER Award (2024).

Publications span ICML, NeurIPS, and top journals like Annals of Statistics. Notable recent work includes FactTest (2024) for LLM factuality testing and Fair Risk Control (2024) for multi-group fairness. Awards include the Presidential Teaching Excellence Fellowship (2024).

Advising over 10 doctoral students and research interns, he co-leads FSRM and Data Science programs at Rutgers. Active in academic service, including editorial roles at Statistica Sinica and conference organization on differential privacy topics.