January 20, 2003
Jack Vevea is a quantitative psychologist with research interests in
applied statistics, item response theory, mathematical models for bias
in memory, and statistical methods for meta-analysis. He specializes in
developing new statistical and mathematical models for psychological research.
Vevea has developed models that combat the problem of publication bias
in large meta-analytic data sets, and he is currently developing similar
methods for smaller-scale analyses.
Vevea earned his undergraduate degree in Greek from UC Berkeley and his doctorate in measurement, evaluation, and statistical analysis from the Department of Education at the University of Chicago. Prior to his appointment at UCSC, Vevea held a faculty position at the University of North Carolina at Chapel Hill.
Wang-Chiew Tan studies various aspects of database problems, including methods and issues related to the tracking of the provenance of data. She has also worked on problems related to data integration, database query languages, scientific databases, and combinatorial optimization on database problems. Tan received a B.S. degree in computer science from the National University of Singapore, and M.S. and Ph.D. degrees in computer science from the University of Pennsylvania. Tan joined the UCSC faculty after graduating from the University of Pennsylvania.