University of Mary Washington - Computer Science
Senior Scientific & Technical Manager for Naval Data Sciences at Naval Surface Warfare Center Dahlgren Division
Research
Jeffrey
Solka
Dahlgren, Virginia
I have a great deal of experience in statistics, mathematics, computer science and the interface between these three disciplines. My goal is to develop techniques to analyze high dimensional data. I am particularly interested in technology watch and horizon scanning.
Specialties: computational statistics, statistical pattern recognition, technology watch and horizon scanning
Part time Adjunct Professor
I teach part time for the Department of Bioinformatics. I teach Biostatistics and Gene Expression Analysis.
Part time adjunct professor.
I teach in the Department of Computer Science.
Principal Scientist
I conduct research and development in statistics, mathematics, computer science, statistical pattern recognition, and technology watch/horizon scanning.
Senior Scientific & Technical Manager for Naval Data Sciences
Coordination of Naval research, development, and prototyping in Naval Data Sciences including activities in statistics, artificial intelligence, and machine learning.
M.S.
Mathematics
M.S.
Physics
Ph.D.
Computational Statistics
My dissertation director was Edward Wegman. My dissertation was in the area of visualization of semiparamteric mixture-based probability density estimates.
Part time Adjunct Professor
I teach part time for the Department of Bioinformatics. I teach Biostatistics and Gene Expression Analysis.
Journal of Multivariate Analysis
The goal of this paper is to give explicit procedures and equations for performing metric multidimensional scaling to surfaces. More specifically, we describe a method for determining a configuration of points in a closed and orientable surface (i.e., the MDS space) for which the interpoint distances closely approximate a given set of dissimilarities. More generally, these constant sectional curvature surfaces are examples of space forms (spaces which are quotients of Euclidean, spherical, or hyperbolic space by a subgroup of the isometry group of the space). We will cast our work in this language, thereby allowing the theory to easily be generalized to higher dimensions.
Journal of Multivariate Analysis
The goal of this paper is to give explicit procedures and equations for performing metric multidimensional scaling to surfaces. More specifically, we describe a method for determining a configuration of points in a closed and orientable surface (i.e., the MDS space) for which the interpoint distances closely approximate a given set of dissimilarities. More generally, these constant sectional curvature surfaces are examples of space forms (spaces which are quotients of Euclidean, spherical, or hyperbolic space by a subgroup of the isometry group of the space). We will cast our work in this language, thereby allowing the theory to easily be generalized to higher dimensions.
Chapman and Hall/CRC Computer Science and Data Analysis
This book offers a good introduction at the advanced undergraduate or graduate level to exploratory data analysis using MATLAB. Numerous example are provided along with the associated code.