Scotland C. Leman

Scotland Leman is an associate professor at Virginia Tech in the Department of Statistics.  He received his Ph.D. from the Department of Statistical Science at Duke University.  He earned a master of science degree in computational from Stanford 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
Research Areas:
  • iconVisual Analytics
Phone: 540-231-5441
Web site
Email

Projects

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

Sponsors

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