Sunday, September 21, 2014
board on mathematical sciences and their applications The National Academies
National Academy of Sciences National Academy of Engineering Institute of Medicine National Research Council
About BMSA
Current Themes
Committee On Applied & Theoretical Statistics
Member Bios
Past Events
Staff and Contact Info


Statement of Task

The National Research Council established the Committee on Applied and Theoretical Statistics (CATS) in 1978 to provide a locus of activity and concern for the statistical sciences, statistical education, use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.

Current CATS Activities:

CATS Brochure in PDF 


Member Biographies


Constantine Gatsonis
Brown University
Dr. Gatsonis joined Brown University in 1995 and became the founding Director of the Center for Statistical Sciences. He is a leading authority on the design and analysis of clinical trials of diagnostic and screening modalities and has extensive involvement in methodologic research in medical technology assessment and in health services and outcomes research. He is Group Statistician of the American College of Radiology Imaging Network (ACRIN), an NCI-funded collaborative group conducting multi-center studies of diagnostic imaging and image-guided therapy for cancer. In his ACRIN work, Dr. Gatsonis is the chief statistician of the Digital Mammography Imaging Screening Trial (a national study comparing digital to film mammography) and is also the chief statistician for ACRIN’s arm of the National Lung Screening Trial (NLST). Dr Gatsonis was the lead statistician of the International Breast MRI Consortium and of the Radiologic Diagnostic Oncology Group (RDOG). He is the founding editor-in-chief of Health Services and Outcomes Research Methodology and serves as a deputy editor of Academic Radiology and a member of the editorial board of Clinical Trials. Dr Gatsonis is an elected Fellow of the American Statistical Association and of the Association for Health Services Research.

Montserrat (Montse) Fuentes
North Carolina State University
Dr. Fuentes is Head and Full professor of Statistics (with tenure) at North Carolina (NC) State. Dr. Fuentes received her B.S. in Mathematics and Music (piano performance) from the University of Valladolid (Spain), and her Ph.D. in Statistics from the University of Chicago (1999). Dr. Fuentes has authored over 60 scientific publications & served as principal investigator (or co-PI) on 20 research grants, with total funding of more than $15 million. Dr. Fuentes was named an American Statistical Association (ASA) fellow (2008) for outstanding contributions to research in spatial statistics, for excellence in the development and application of statistical methodology in atmospheric sciences, air pollution and oceanography; and for service to the profession. She is the editor of the Journal of Agricultural, Biological, and Environmental Statistics (JABES), of the International Biometrics Society. Dr. Fuentes is a member-elect of the International Statistical Institute, and has been a member of the Regional Advisory Board (RAB) for the Eastern North American Region (ENAR) of the International Biometric Society. Dr. Fuentes is a member of the Science Advisory Board (SAB) Integrated Human Exposure Committee of the U.S. Environmental Protection Agency, and the U.S. representative in the Board of Directors of the International Environmetrics Society. She was a member of the Biostatistical Methods and Research Design (BMRD) study section of the National Institutes for Health, and she is currently a member of the scientific review committee of Health Canada. She has also worked for the U.S. Department of Justice as an expert witness, and was a member of a committee of the National Research Council of the National Academies working on the impact of ozone on mortality. She is a senior leader of the ADVANCE-NSF Developing Diverse Departments program at NCSU.

Alfred O. Hero III
University of Michigan
Dr. Hero is the R. Jamison and Betty Williams Professor of Engineering at the University of Michigan. He received the B.S. (summa cum laude) from Boston University (1980) and PhD from Princeton University (1984), both in Electrical Engineering. His primary appointment is in the Department of Electrical Engineering and Computer Science and he also has appointments, by courtesy, in the Department of Biomedical Engineering and the Department of Statistics. In 2008 he was awarded the Digiteo Chaire d'Excellence, sponsored by Digiteo Research Park in Paris, located at the Ecole Superieure d'Electricite, Gif-sur-Yvette, France. He is an IEEE Fellow and several of his research articles have received best paper awards. Prof. Hero was awarded the University of Michigan Distinguished Faculty Achievement Award (2011). He received the IEEE Signal Processing Society Meritorious Service Award (1998) and the IEEE Third Millenium Medal (2000). He was President of the IEEE Signal Processing Society (2006-2008) and was on the Board of Directors of the IEEE (2009-2011) where he served as Director of Division IX (Signals and Applications). Dr. Hero’s recent research interests have been in detection, classification, pattern analysis, and adaptive sampling for spatio-temporal data. Of particular interest are applications to network security, multi-modal sensing and tracking, biomedical imaging, and genomic signal processing.

David M. Higdon
Los Alamos National Laboratory
Dr. Higdon is a member of the Statistical Sciences Group at the Los Alamos National Laboratory. He is an internationally recognized expert in Bayesian statistical modeling of environmental and physical systems. He has also led numerous programmatic efforts at LANL in the quantification of margins and uncertainties and uncertainty quantification. His recent research has focused on simulation-aided inference in which physical observations are combined with computer simulation models for prediction and inference. His research interests include space-time modeling; inverse problems in physics, hydrology, and tomography; inference based on the combining of deterministic and stochastic models; multiscale models; parallel processing in posterior exploration; statistical modeling in physical, environmental, and biological sciences; and Monte Carlo and simulation-based methods. He received a B.A. and M.A. in Mathematics from University of California, San Diego and a Ph.D. in Statistics from University of Washington.

Iain Johnstone
Stanford University
Dr. Johnstone is a professor in the Departments of Statistics and of Health Research and Policy (Biostatistics) at Stanford University. His research interests include statistical decision theory, wavelet-like methods in estimation theory, and multivariate analysis. Dr. Johnstone was elected to the National Academy of Sciences in 2005 for his fundamental contributions to the understanding of statistical procedure for the analysis of the enormously complex and multidimensional data that are arising in many fields. He previously served on the Board on Mathematical Sciences and Their Applications. He holds a M.Sc. in probability and statistics and a B.Sc. in pure mathematics and statistics from Australian National University, and an M.S. and a Ph.D. in statistics from Cornell University.

Robert E. Kass
Carnegie Mellon University
Dr. Kass is a Professor in the Department of Statistics at Carnegie Mellon University. He received his Ph.D. in Statistics from the University of Chicago. Kass has served as Chair of the Section for Bayesian Statistical Science of the American Statistical Association, Chair of the Statistics Section of the American Association for the Advancement of Science, Executive Editor of the international review journal Statistical Science, and founding Editor-in-Chief of the journal Bayesian Analysis. He is an elected Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science. He has been recognized by the Institute for Scientific Information as one of the 10 most highly cited researchers, 1995-2005., in the category of mathematics. In 1991 he began the series of workshops Case Studies in Bayesian Statistics, which are held at Carnegie Mellon every odd year, and was co-editor of the six proceedings volumes that were published by Springer. He is coorganizer of the workshop series Statistical Analysis of Neuronal Data, which began in 2002 and is held at Carnegie Mellon on even years. Kass has been been on the faculty of the Department of Statistics at Carnegie Mellon since 1981 and served as Department Head from 1995 to 2004; he joined the Center for the Neural Basis of Cognition in 1997, and the Machine Learning Department in 2007.

John Lafferty
The University of Chicago
Dr. Lafferty is the Louis Block Professor in the Departments of Statistics, Computer Science, and the College at The University of Chicago. His research area is machine learning, with a focus on computational and statistical aspects of nonparametric methods, high-dimensional data, graphical models, and applications. An associate editor of the Journal of Machine Learning Research, Dr. Lafferty served as progam co-chair and general co-chair of the Neural Information Processing Systems Foundation conferences in 2009 and 2010. Dr. Lafferty received his doctoral degree in mathematics from Princeton University, where he was a member of the Program in Applied and Computational Mathematics. Prior to joining the University of Chicago in 2011, he was Professor of Computer Science, Machine Learning, and Statistics at Carnegie Mellon University, where he is currently an Adjunct Professor.

Xihong Lin
Harvard University
Xihong Lin is a Professor of Biostatistics at Harvard University. She received a PhD from the University of Washington. Dr. Lin's major statistical research interests lie in developing statistical methods for high-dimensional and correlated data. She is particularly interested in developing statistical and computational methods for "omics" data in population-based studies, such as genetic epidemiology, genetic environmental sciences and clinical studies. She currently serves as the coordinating director of the Program of Quantitative Genomics of Harvard School of Public Health. Dr. Lin's specific areas of statistical research include statistical learning methods for high-dimensional data, dimension reduction, variable selection, nonparametric and semiparametric regression models, measurement error, mixed (frailty) models, estimating equations, and missing data. Dr. Lin's areas of applications include cancer, genetic epidemiology, gene and environment, genome-wide association studies, genomics in population science, biomarkers and proteomics.

Sharon-Lise T. Normand
Harvard University
Dr. Normand is Professor of Health Care Policy (Biostatistics) in the Department of Health Care Policy at Harvard Medical School and Professor in the Department of Biostatistics at the Harvard School of Public Health. Her research focuses on the development of statistical methods for health services and outcomes research, primarily using Bayesian approaches, including causal inference, provider profiling, item response theory, latent variables analyses, multiple informants analyses, and evaluation of medical devices in randomized and non-randomized settings. She serves on several task forces for the American Heart Association and the American College of Cardiology, was a consultant to the US Food and Drug Administration’s Circulatory System Devices Advisory Panel after serving a four-year term on the panel, is a member of the Medicare Evidence Development and Coverage Advisory Committee, and is Director of Mass-DAC, a data coordinating center that monitors the quality of all adult cardiac surgeries and coronary interventions in all Massachusetts’ acute care hospitals. Dr. Normand was the 2010 President of the Eastern North American Region of the International Biometrics Society and is Vice Chair of the Patient Centered Outcomes Research Institute’s Methodology Committee. Dr. Normand earned her Ph.D. in Biostatistics from the University of Toronto, holds a Masters of Science as well as a Bachelor of Science degree in Statistics, and completed a post-doctoral fellowship in Health Care Policy at Harvard Medical School. She is a Fellow of the American Statistical Association, a Fellow of the American College of Cardiology, a Fellow of the American Heart Association, and an Associate of the Society of Thoracic Surgeons. In 2011, Dr. Normand was awarded the American Statistical Association Health Policy Statistics Section’s Long Term Excellence Award.

Giovanni Parmigiani
Harvard University
Dr. Parmigiani is a Professor of Biostatistics in the Department of Biostatistics at the Harvard School of Public Health. He is also the Chair of the Department of Biostatistics and Computational Biology at the Dana Farber Cancer Institute and the Associate Director for Population Sciences of the Dana-Farber/Harvard Cancer Center. He received a B.S. in Economics and Social Sciences at Università L. Bocconi, and a M.S. and a Ph.D. in Statistics from Carnegie Mellon University. His research interests include models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer, specifically with respect to breast, ovarian, colorectal, pancreatic and skin cancer. His research covers statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects, integration of genomic information across technologies, and cross-study validation of genomics results. He is also interested in statistical methods for complex medical decisions, comprehensive models for lifetime history of chronic disease outcomes, decision trees, and dynamic programming. This includes Bayesian modeling and computation, multilevel models, decision theoretic approaches to inference, sequential experimental design, and Markov chain Monte Carlo methods.

Raghu Ramakrishnan
Dr. Ramakrishnan is a technical fellow at Microsoft, and CTO for Information Service. He received a B.Tech. from IIT Madras and a Ph.D. from the University of Texas at Austin. He was a professor at the University of Wisconsin-Madison from 1987- 2006, and co-founded the UW Data Mining Institute. From 2006 to 2012 he was a Yahoo! Fellow, which helped establish Yahoo! Labs, and as Chief Scientist for the portal, cloud computing, and search divisions, led the development of content recommendation algorithms (CORE), cloud data stores (PNUTS), and semantic search (“Web of Things”). In 1999, he founded QuiQ, a company that introduced a cloud-based crow-sourcing service for collaborative customer support and knowledge management, used by Ask Jeeves, Business Objects, Compaq, Sun, and others. His research in the area of databases, with a focus on data mining and query optimization, has been used in various commercial database systems. He led the CORAL project, which led to a widely used deductive database system and contributed to recursive query language extensions in the SQL:1999 standard. His work on extending SQL to deal with queries over sequences influenced the design of window functions in SQL:1999. His group at the University of Wisconsin was among the first to address mining of continuously evolving and streaming data, and developed scalable algorithms for clustering, decision-tree construction, and itemset counting.

Ernest Seglie
Office of the Secretary of Defense (retired)
Mr. Seglie is a retired science advisor of the Office of the Secretary of Defense, Operational Test and Evaluation. His responsibilities included providing “scientific and technical guidance on the overall approach to DoD evaluation of the operational effectiveness and suitability of major DoD weapons systems.” He received a BS in physics from The Cooper Union and a PhD in theoretical nuclear physics from University of Massachusetts in 1972. He taught at Rensselaer Polytechnic Institute and Yale University before joining the Institute for Defense Analyses in 1979. He received the Andrew J. Goodpaster Award for Excellence in Research in 1987, the International Test and Evaluation Association 2009 Allen R. Matthews Award for “leadership and technical contributions to the evaluation of operational effectiveness and suitability,” and the National Defense Industrial Association Walter W. Hollis Award in 2009. In addition, he was recipient of the President of the United States Rank Conferral of Meritorious Senior Professional in 2003 and the Secretary of Defense Medal for Meritorious Civilian Service in 2010, which included mention that he “led the drive to apply statistical methods to test design and evaluation.” Recent areas of interest include test and evaluation policy in the Department of Defense, and reliability.

Lance Waller
Emory University
Dr. Waller is Rollins Professor and Chair of the Department of Biostatistics and Bioinformatics in the Rollins School of Public Health at Emory University. He received a Ph.D. in Operations Research from Cornell University in 1992. Dr. Waller's research involves the development of statistical methods to analyze spatial and spatio-temporal patterns. Past research involves the assessment of spatial clustering of disease, linking spatial statistics and geographic information systems, statistical assessments of environmental justice, and hierarchical Bayesian methods for modeling small-area health statistics. Recent areas of interest include spatial point process methods in alcohol epidemiology, conservation biology, and hierarchical models in disease ecology. Dr. Waller was the recipient of the 2004 Abdel El-Shaarawi Young Researcher’s Award. Dr. Waller has served on multiple National Academies committees including the National Research Council Committee on the Review of Existing and Potential Stando? Explosives Detection Techniques, the Institute of Medicine Committee on the Utility of Proximity-based Herbicide Exposure Assessments in Epidemiologic Studies in Vietnam Veterans, the National Academies Committee To Assess Potential Health E?ects from Exposures to PAVE PAWS Low-level Phased-array Radiofrequency Energy, and the National Academies Committee on Analysis Of Cancer Risks in Populations Near Nuclear Facilities: Phase 1.

Eugene Wong
University of California, Berkeley
Dr. Wong is a Professor Emeritus in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He received B.S., A.M., and Ph.D. degrees in Electrical Engineering from Princeton University. In 1980, he co-founded Relational Technology, Inc., later renamed the INGRES Corporation, which was a leading provider of database software products. While in Hong Kong from 1994-1996, he was instrumental in building an Internet backbone for Asia, first as CEO of SuperNet, Ltd., and then as founder of the Asia Internet Holding Company. From 1998-2005, he was variously a director, chief scientist, and CEO of Versata, Inc., a public software company serving the distributed enterprise applications market. He served as an Associate Director of OSTP and Associate Director of NSF for Engineering, which gives him a good perspective for evaluating the usefulness of this report in federal policy circles. He is a member of the National Academy of Engine