James Shine
James Shine
M.S., Ph.D.
Professional Lecturer
Part-time Faculty
Department: Biostatistics and Bioinformatics
Contact:
Email:
James Shine
Office Phone:
202-994-3399
Science & Engineering Hall
800 22nd Street, NW
Washington DC 20052
Dr. Shine is an Adjunct Professor of the Department of Biostatistics and Bioinformatics. He teaches introductory biostatistics course for both undergraduate and graduate students in the School of Public Health. Dr. Shine performed topographic research for the US Government for over 30 years.
EXPERTISE:
Biostatistics
EDUCATION:
Ph.D., Computational Statistics, George Mason University, 2003
M.S., Statistical Science, George Mason University, 1996
B.A., Mathematics, University of Virginia, 1979
B.A., Chemistry, University of Virginia, 1979
TEACHING:
BIOL 214, Introduction to Biostatistics, George Mason University, Fall 2013
PUBH 2142, Introduction to Biostatistics for Public Health, Spring 2022, Fall 2022, Spring 2023
PUBH 6002, Biostatistical Applications for Public Health, Summer 2022, Fall 2022
RESEARCH:
During his government career, Dr. Shine did research in digital image processing and classification, expert systems, advanced and parallel computing models, neural networks, genetic algorithms, spatial and spatio-temporal statistics, spatial data mining, image compression, and evidential reasoning. He has also done non-government research in sensor anomaly detection, geographic clustering, and pattern identification in time series.
PUBLICATIONS:
Shine, J. and Gentle, J., “Nonparametric Smoothing of Time Series”, Proceedings of 2020 Joint Statistical Meetings, August 2020.
Mohan, P., Shekhar, S., Shine, J., and Rogers, J., "Cascading spatio-temporal pattern discovery", IEEE Journal on Transactions on Knowledge and Data Engineering, November 2012
Shine, J. and Gentle, J., “Alarm activation, pattern discovery, and anomaly detection in sensor networks”, WIREs Computer Statistics, Wiley Periodicals, 2012.
Shine, J., Rogers,J., Shekhar, S. and Celik, M.,”Discovering Patterns of Insurgency via Spatio-Temporal Data Mining”, Army Science Conference, Orlando, FL, December 2008.
Celik, M., Rogers, J., Shekhar, S., and Shine, J., “Mixed-Drove Spatio-Temporal Co-occurrence Pattern Mining”, IEEE Journal of Transactions in Knowledge and Data Engineering (TKDE), Volume 20 # 10 pp. 1322-1335, October 2008.
Shine, J. Rogers, S. Shekhar and M. Celik, “Temporal Extensions to Spatial Statistical Metrics”,Proceedings of the 2007 Joint Statistical Meetings, Salt Lake City, UT, August 2007.
Shine, J., Krause, P., and Flood, K., &Spatio-Temporal Prediction of Iraqi Events", Proceedings of the Army Conference on Applied Statistics, Raleigh, NC, October 2006.
Oliver, M., Shine, J., and Slocum, K., “Using the Variogram to Explore Imagery of Two Different Spatial Resolutions“, International Journal of Remote Sensing, Volume 26, No. 15, August 2005, pp. 3225-3240.
Shine, J. and Carr, D., “Relationships between Land Cover and Spatial Statistical Compression in High-Resolution Imagery”, 34 th Conference on the Interface, April 2002, Montreal, Canada.
Shine, J. and Krause, P., “Exploration and Estimation of North American Climatological Data”, 32nd Conference on the Interface, April 2000, New Orleans, LA.
Shine, J., “Mapping and Modeling 1-Meter Multispectral Imagery Data”,Proceedings of the Joint Statistical Meetings 2000, August 2000, Indianapolis, IN.
Shine, J.,“A Genetic Algorithm Approach for Configuring Backpropagation Architectures for Imagery Classification”, World Congress on Neural Networks, July 1995, Washington, D.C.
Shine, J., “Bayesian, Evidence, Fuzzy: Which Theory Works Best When Reasoning with Uncertain Knowlege?”
American Society of Photogrammetry-American Congress on Surveying and Mapping Convention, March 1985.