James Booth is a Professor and Department Chair in the Department of Statistics and Data Science at Cornell University, part of the Computing and Information Science school. He holds a joint appointment with the Department of Biological Statistics and Computational Biology in the College of Agricultural and Life Sciences. His research focuses on statistical methodology, including bootstrap methods, clustering, mixed models, and applications in bioinformatics. He has taught numerous courses, including Statistical Methods II and Biological Statistics I, and contributes to Cornell's statistical consulting service. His work spans statistical theory and applications across disciplines like epidemiology and social sciences. Education: PhD from the University of Florida (Department of Statistics), with postdoctoral research at the Australian National University and Colorado State University. Research Interests: James’ methodological work emphasizes computational statistics, including Monte Carlo methods and generalized linear models. His applied research includes bioinformatics, wildlife disease surveillance, and social science data analysis. Key contributions include Bayesian modeling for disease prevalence estimation and statistical tools for proteomic data analysis. Publications: Over 50 peer-reviewed articles, with recent focuses on sample size calculations for wildlife disease studies and statistical methodologies for high-dimensional data. Notable work includes contributions to the Journal of the American Statistical Association and PLoS Computational Biology. Advising: Advised over 15 graduate students, many contributing to statistical methodology and interdisciplinary applications. Labs/Teams: Active in the Cornell Statistical Consulting Unit and collaborates with interdisciplinary groups in biology, public health, and social sciences.
