Ph.D.: Biostatistics, University of Washington
MBA: University of Texas at Austin
Research Interests: Breast cancer risk prediction, misclassification of mammographic breast density, modeling of mammographic breast density, and maternal and child health.
Ph.D.: Biostatistics, University of Washington
MBA: University of Texas at Austin
Research Interests: Breast cancer risk prediction, misclassification of mammographic breast density, modeling of mammographic breast density, and maternal and child health.
Refik Soyer is chair and professor of decision sciences and of statistics at the George Washington University (GW). He is the Mitch Blaser Distinguished Scholar in Business Analytics. He also serves as the director of the Institute for Integrating Statistics in Decision Sciences at GW. He received his DSc in operations research from GW, MSc in operational research from the University of Sussex, England and BA in economics from Bogazici University, Turkey. His area of interests are Bayesian statistics and decision analysis, stochastic modeling, statistical aspects of reliability analysis, and time series analysis. He has published over 100 articles and directed or co-directed 13 doctoral dissertations. His work has appeared in journals such as Journal of the American Statistical Association, Journal of the Royal Statistical Society, Ser. B., Technometrics, Biometrics, Journal of Econometrics, Statistical Science, International Statistical Review, Annals of Applied Statistics and Management Science. He has also co-edited a volume titled Mathematical Reliability: An Expository Perspective. His research was supported by Army Research Office, National Science Foundation and Office of Naval Research. Soyer is an elected member of the International Statistical Institute, Fellow of the Turkish Statistical Association and a Fellow of the American Statistical Association. He was a vice president of the International Association for Statistical Computing. He served on the editorial board of the Journal of the American Statistical Association and is currently an associate editor of the Applied Stochastic Models in Business and Industry.
Research areas of expertise:
Bayesian Statistics
Stochastic Modeling
Decision Analysis
Reliability Modeling and Analysis
Time Series Analysis
Refik Soyer is chair and professor of decision sciences and of statistics at the George Washington University (GW). He is the Mitch Blaser Distinguished Scholar in Business Analytics. He also serves as the director of the Institute for Integrating Statistics in Decision Sciences at GW. He received his DSc in operations research from GW, MSc in operational research from the University of Sussex, England and BA in economics from Bogazici University, Turkey. His area of interests are Bayesian statistics and decision analysis, stochastic modeling, statistical aspects of reliability analysis, and time series analysis. He has published over 100 articles and directed or co-directed 13 doctoral dissertations. His work has appeared in journals such as Journal of the American Statistical Association, Journal of the Royal Statistical Society, Ser. B., Technometrics, Biometrics, Journal of Econometrics, Statistical Science, International Statistical Review, Annals of Applied Statistics and Management Science. He has also co-edited a volume titled Mathematical Reliability: An Expository Perspective. His research was supported by Army Research Office, National Science Foundation and Office of Naval Research. Soyer is an elected member of the International Statistical Institute, Fellow of the Turkish Statistical Association and a Fellow of the American Statistical Association. He was a vice president of the International Association for Statistical Computing. He served on the editorial board of the Journal of the American Statistical Association and is currently an associate editor of the Applied Stochastic Models in Business and Industry.
Research areas of expertise:
Bayesian Statistics
Stochastic Modeling
Decision Analysis
Reliability Modeling and Analysis
Time Series Analysis
Zhen Chen, Ph.D., is a senior investigator in NICHD’s Biostatistics and Bioinformatics Branch. Prior to joining NICHD in 2008, Dr. Chen was a tenure-track assistant professor in the Department of Biostatistics and Epidemiology at the University of Pennsylvania. He has published numerous papers in biomedical research and is the recipient of several NIH and NICHD merit awards.
With a Ph.D. from the University of Connecticut, Dr. Chen has research interests in Bayesian modeling and computations, diagnostic accuracy, causal inference, and chemical mixture modeling.
Zhen Chen, Ph.D., is a senior investigator in NICHD’s Biostatistics and Bioinformatics Branch. Prior to joining NICHD in 2008, Dr. Chen was a tenure-track assistant professor in the Department of Biostatistics and Epidemiology at the University of Pennsylvania. He has published numerous papers in biomedical research and is the recipient of several NIH and NICHD merit awards.
With a Ph.D. from the University of Connecticut, Dr. Chen has research interests in Bayesian modeling and computations, diagnostic accuracy, causal inference, and chemical mixture modeling.
David Banks obtained an M.S. in Applied Mathematics from Virginia Tech in 1982, followed by a Ph.D. in Statistics in 1984. He won an NSF Postdoctoral Research Fellowship in the Mathematical Sciences, which he took at Berkeley. In 1986 he was a visiting assistant lecturer at the University of Cambridge, and then joined the Department of Statistics at Carnegie Mellon in 1987. In 1997 he went to the National Institute of Standards and Technology, then served as chief statistician of the U.S. Department of Transportation, and finally joined the U.S. Food and Drug Administration in 2002. In 2003, he returned to academics at Duke University.
David Banks was the coordinating editor of the Journal of the American Statistical Association. He co-founded the journal Statistics and Public Policy and served as its editor. He co-founded the American Statistical Association's Section on National Defense and Homeland Security, and has chaired that section, as well as the sections on Risk Analysis and on Statistical Learning and Data Mining. In 2003 he led a research program on Data Mining at the Statistical and Applied Mathematical Sciences Institute; in 2008, he led a research program at the Isaac Newton Institute on Theory and Methods for Complex, High-Dimensional Data; in 2012, he led another SAMSI research program, on Computational Advertising. He has published 74 refereed articles, edited eight books, and written four monographs.
David Banks is past-president of the Classification Society, and has twice served on the Board of Directors of the American Statistical Association. He is currently the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently won the American Statistical Association's Founders Award.
His research areas include models for dynamic networks, dynamic text networks, adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis.
David Banks obtained an M.S. in Applied Mathematics from Virginia Tech in 1982, followed by a Ph.D. in Statistics in 1984. He won an NSF Postdoctoral Research Fellowship in the Mathematical Sciences, which he took at Berkeley. In 1986 he was a visiting assistant lecturer at the University of Cambridge, and then joined the Department of Statistics at Carnegie Mellon in 1987. In 1997 he went to the National Institute of Standards and Technology, then served as chief statistician of the U.S. Department of Transportation, and finally joined the U.S. Food and Drug Administration in 2002. In 2003, he returned to academics at Duke University.
David Banks was the coordinating editor of the Journal of the American Statistical Association. He co-founded the journal Statistics and Public Policy and served as its editor. He co-founded the American Statistical Association's Section on National Defense and Homeland Security, and has chaired that section, as well as the sections on Risk Analysis and on Statistical Learning and Data Mining. In 2003 he led a research program on Data Mining at the Statistical and Applied Mathematical Sciences Institute; in 2008, he led a research program at the Isaac Newton Institute on Theory and Methods for Complex, High-Dimensional Data; in 2012, he led another SAMSI research program, on Computational Advertising. He has published 74 refereed articles, edited eight books, and written four monographs.
David Banks is past-president of the Classification Society, and has twice served on the Board of Directors of the American Statistical Association. He is currently the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently won the American Statistical Association's Founders Award.
His research areas include models for dynamic networks, dynamic text networks, adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, forensics, and certain topics in high-dimensional data analysis.
Research Interests:
Survival analysis, Epidemiologic methods, Stochastic processes, Phylogenetics and casual inference
Education:
ScD, Epidemiology, Harvard School of Public Health 2008
MS, Biostatistics, Harvard School of Public Health 2008
BA, Harvard University 2001
Research Interests:
Survival analysis, Epidemiologic methods, Stochastic processes, Phylogenetics and casual inference
Education:
ScD, Epidemiology, Harvard School of Public Health 2008
MS, Biostatistics, Harvard School of Public Health 2008
BA, Harvard University 2001
Wayne Folta enjoys diving into a new problem space, working with customers to clarify their needs and objectives, and using sophisticated tools and analysis to turn their data into insights. His major technical interests are time-series and predictive analytics. Previously, Wayne developed software in the intelligence community as a government employee and a contractor, and worked in the non-profit world as a video producer. Wayne volunteers in his community, teaching and providing statistical consulting for the local library and others.
Wayne earned a Master's Degree in Computer Science (Artificial Intelligence) from George Mason University, and is also an alumnus of the University of Maryland and the Rochester Institute of Technology.
Wayne enjoys snowboarding, the ancient game of Go, and learning R packages and other statistical tools.
Wayne Folta enjoys diving into a new problem space, working with customers to clarify their needs and objectives, and using sophisticated tools and analysis to turn their data into insights. His major technical interests are time-series and predictive analytics. Previously, Wayne developed software in the intelligence community as a government employee and a contractor, and worked in the non-profit world as a video producer. Wayne volunteers in his community, teaching and providing statistical consulting for the local library and others.
Wayne earned a Master's Degree in Computer Science (Artificial Intelligence) from George Mason University, and is also an alumnus of the University of Maryland and the Rochester Institute of Technology.
Wayne enjoys snowboarding, the ancient game of Go, and learning R packages and other statistical tools.
