Phillip B. Stark

Philip B. Stark

Title
Professor of Statistics
Department
Dept of Statistics
Phone
(510) 394-5077
Research Expertise and Interest
astrophysics, law, statistics, litigation, causal inference, inverse problems, geophysics, elections, uncertainty quantification, educational technology
Research Description

I study inference problems and uncertainty quantification with applications including causal inference, climate, cosmology, earthquake forecasts, elections, endangered species, food webs, gender bias, geomagnetism, geriatric hearing loss, information retrieval, Internet content filters, legislation and litigation, risk assessment, seismic structure of Sun and Earth, spectrum estimation, and urban foraging as a source of nutrition in "food deserts." I developed methods for auditing elections now in law in California, Colorado, and Rhode Island. I developed or co-developed methods that are part of the data pipelines of the Øersted geomagnetic satellite and the Global Oscillations Network Group. I have consulted for major corporations and for the U.S. Department of Justice, the Federal Trade Commission, the U.S. Department of Agriculture, the U.S. Census Bureau, the U.S. Department of Housing and Urban Development, the U.S. Department of Veterans Affairs, the California Attorney General, the California Highway Patrol, and the Illinois State Attorney. I have testified to the U.S. House of Representatives Subcommittee on the Census; the State of California Senate Committee on Elections, Reapportionment and Constitutional Amendments; the State of California Assembly Committee on Elections and Redistricting; and the State of California Senate Committee on Natural Resources. See www.stat.berkeley.edu/~stark/bio.htm 

In the News

April 26, 2010

California Assembly committee endorses statistician's election auditing method

Since 1965, California counties have been required to hand tally one percent of all ballots after an election to validate the machine count, despite the fact that available auditing techniques lack any statistical basis. UC Berkeley's Philip Stark has now provided statistically sound methods for conducting these audits, and a proposed bill, AB 20203, will establish a statewide pilot program to test these methods.