Scotland C. Leman

Scotland Leman is associate professor in the Department of Statistics at Virginia Tech and core faculty at the Sanghani Center.

His main 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.
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.
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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