Jay Emerson

Science (Statistics and Data Science)

Visiting Professor
Professor Adjunct and Director of Graduate Studies, Department of Statistics and Data Science, Yale University

Email: john.emerson@yale-nus.edu.sg
Email: john.emerson@yale.edu
Website: http://www.stat.yale.edu/~jay/

View Curriculum Vitae

Professor John W. Emerson (Jay) is Director of Graduate Studies in the Department of Statistics and Data Science at Yale University. He teaches a range of graduate and undergraduate courses at Yale as well as workshops, tutorials and short courses at all levels around the world. His primary interests are in computational statistics and graphics, and his applied work ranges from topics in sports statistics to bioinformatics, environmental statistics, and Big Data challenges. He is the author of several R packages including Bayesian change point analysis (BCP), bigmemory and sister packages (towards a scalable solution for statistical computing with massive data), and generalised pairs plots (gpairs). He has served in various leadership roles in several sections of the American Statistical Association, and is an Editor of the Journal of Statistical Software.

Statistical computing; data analysis; Bayesian statistics; visualization; environmental performance and sustainability.

Esty, Daniel C., and John W. Emerson (2018). “From Crisis and Gurus to Science and Metrics: Yale’s Environmental Performance Index and the Rise of Data-Driven Policymaking.” In Routledge Handbook on Sustainability Indicators.

Kane, Michael J., John W. Emerson, and Stephen Weston (2013). “Scalable Strategies for Computing with Massive Data.” Journal of Statistical Software 55.14: 1-19.

Emerson, John W. and Taylor Arnold (2011). “Statistical Sleuthing by Leveraging Human Nature: A Study of Olympic Figure Skating.” The American Statistician, 65 (3), 143-148.

QR Core and 4212: Statistical Case Studies (with R)