Research Bio

Philip B. Stark is a statistician whose research focuses on uncertainty quantification, risk assessment, election auditing, and reproducible science. He develops statistical methods that provide rigorous confidence measures in scientific and policy contexts, from physical science to clinical trials to public health. Stark’s work on risk-limiting audits has transformed election verification practices in the United States. His research promotes transparency, trustworthiness, and accountability in data-driven decision-making. 

He is Professor of Statistics at UC Berkeley. A member of the American Academy of Arts and Sciences and fellow of the American Statistical Association and the Institute of Physics, he mentors students in applied statistics, data ethics, and scientific integrity.

Research Expertise and Interest

elections, astrophysics, law, statistics, litigation, causal inference, inverse problems, geophysics, uncertainty quantification, educational technology, soil science, race and gender bias and discrimination, nonparametrics, climate, natural disasters, sustainable food systems, public impact research/scholarship, community-engaged research / scholarship, community-based research partnerships, social justice research, research in the public interest, active transportation, earthquake hazard mitigation, natural hazards