Scotland C. Leman

Scotland Leman is associate professor in the Department of Statistics at Virginia Tech. He earned a master of science degree in computational from Stanford University and his Ph.D. from the Department of Statistical Science at Duke University

His core research interests include Bayesian statistics on both a theoretical and inferential level; MCMC mixing theory; data augmentation for efficient simulation; and large-scale stochastic modeling. Additionally, he has a strong interest in visualization techniques, which involve Human-Computer-Interaction. More specifically, given visual displays, he is interested in how users can inject feedback so that resulting displays are a merger between the data, visualization model, and the user’s cognitive insights. Such methods prove to be exceedingly useful in exploring relevant information in very high-dimensional spaces.
Associate Professor of Statistics
Research Areas:
  • iconVisual Analytics
Phone: 540-231-5441
Web site


Visual to Parametric Interaction (V2PI) Visual to Parametric Interaction (V2PI) is a non-probabilistic version of BaVA.
Research Areas:
  • iconVisual Analytics
Dates: September 15, 2009April 3, 2017
EMBERS EMBERS is a system for forecasting societal significant societal events from open source surrogates.
Research Areas:
  • iconForecasting
  • iconNetwork Science
Dates: August 1, 2012July 4, 2016


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