معرفی
Jacob Spertus is a postdoctoral researcher in the Department of Statistics at the University of California, Berkeley. He completed his PhD in Statistics at Berkeley in 2024, advised by Philip B. Stark. His work spans interdisciplinary applications including risk-limiting election audits, soil organic carbon measurement, cardiovascular outcomes research, and motor carrier safety. Prior to his PhD, he was a research assistant at Harvard Medical School’s Department of Health Care Policy, working with Sharon-Lise Normand. He holds a Bachelor’s degree in Mathematics from Bowdoin College.
- Education: PhD in Statistics (UC Berkeley, 2024), BA in Mathematics (Bowdoin College, 2016)
His research focuses on causal inference, nonparametric methods, design-based statistics, and policy optimization. He develops statistical tools for environmental science (soil carbon monitoring), election integrity (risk-limiting audits), and healthcare policy (cardiovascular outcomes analysis). His technical work emphasizes rigorous validation and practical implementation of statistical methodologies.
Key contributions include methodologies for stratified sequential inference, optimal sampling designs for soil carbon measurement, and audit techniques to ensure election accuracy. His applied work bridges theoretical statistics with real-world challenges in public policy and scientific measurement.
- Labs/Teams: Collaborates with Philip B. Stark’s research group at Berkeley and previously with Harvard’s Health Care Policy department
