Research Interests

Bayesian statistical modeling with an emphasis in model averaging, kernel regression, and Bayes linear; Uncertainty analysis of computer models/experiments; Data mining coupled with data visualization that promotes human-data interaction; Applications in proteomics, bioinformatics, cosmology, climatology, hydrology, and homeland security.

Select Funded Research

  • Social Determinants of Health Personal Metrics and Population Development; $96,905 for 2018; Co-Principal Investigator; Socially Determined (sociallydetermined. com).

  • NRT-DESE: UrbComp: Data Science for Modeling, Understanding, and Advancing Urban Populations; $2,999,238 for 2015-2020; Co-Principal Investigator; National Science Foundation, Division of Graduate Education; #1545362.

  • BIGDATA: F: DKA: Usable Multiple Scale Big Data Analytics Through Interactive Visualization; $998,912 for 2014-2017; Co-Principal Investigator; the National Science Foundation, Division of Information and Intelligence Systems; #1447416

  • Critical Thinking with Data Visualization (CTDV); $199,943 for 2013-2016; Principal Investigator; the National Science Foundation, Division of Undergraduate Education; #1141096

  • Dimensions: Collaborative Research: Diversity and Symbiosis: Examining the Taxonomic, Genetic, and Functional Diversity of Amphibian Skin Microbiota; $1,205,921 for 2011-2015; Co-Principal Investigator; the National Science Foundation, Division of Environmental Biology; #1136640

  • Bayesian Visual Analytics (BaVA); $499,307 for 2009-2012; Co-Principal Investigator; the National Science Foundation, Division of Computer and Communications Foundations; #0937071

  • Systems Biology of Metabolic Regulation for Rational Metabolic Engineering in Soybean Seeds; $61,000 for April 2010-April 2012; Co-Principal Investigator; United States Department of Agriculture and Virginia Tech College of Agriculture and Life Science

  • Design of Variation: Data Matching/Large Model Methods; $17,364 for October- December 2009;; Principal Investigator; Pratt and Whitney

  • Software/ Additional Material for Papers

  • Here is an R package and vignette for peak identification in MALDI-TOF using Lark. The functions in this package implement the methods in "Nonparametric Models for Peak Identification in MALDI-TOF Mass Spectroscopy": larkPeaks, vignette.

  • Data analyzed in "Expert-Guided Generative Topographical Modeling with Visual to Parameteric Interaction": NIH Data.

  • Here is an R package for filtering variables when there is a Multinomial Response. The functions in this package implement the methods in "Dimension Reduction for Multinomial Models Via a Kolmogorov-Smirnov Measure (KSM)": KSmeasure.

  • Here is a Matlab macro for visualizing sensor data to assess data quality. This macro is described in the paper, "Outlier Detection for Sensor Systems (ODSS): A MATLAB Macro for Evaluating Microphone Sensor Data Quality" : ODSS.
  • Curriculum Vitae

  • pdf