Scientific Advisory Committee

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The Scientific Advisory Committee adjudicates competitions for Collaborative Research Team projects and major workshops and conferences, and makes funding recommendations to the Board. The committee is chaired by the Director of CANSSI, and consists of nine prominent statistical scientists, normally from outside Canada. Each of PIMS, Fields and CRM are entitled to nominate a member of this committee.

Raymond Carroll (term ends 2019)

Raymond Carroll

Raymond J. Carroll (http://www.stat.tamu.edu/~carroll) is Distinguished Professor of Statistics and Nutrition at Texas A&M University (USA), and Distinguished Professor at the University of Technology Sydney (Australia). He has been P.I. of a major NCI grant for the development of statistical methodology since 1990, and became the first statistician to receive the prestigious National Cancer Institute MERIT Award (in 2005). He is the Director of the Texas A&M Institute for Applied Mathematics and Computational Science (http://iamcs.tamu.edu).

Raymond served as editor of Biometrics, the journal of the International Biometric Society, and as editor of the Journal of the American Statistical Association (Theory and Methods). He has won many honours in the profession, including the 1988 COPSS Presidents’ Award, given annually by the North American statistical societies to the outstanding statistician under the age of 40. He gave the Fisher Lecture at the 2002 Joint Statistical Meetings, an award given by the major statistical societies in honour of a senior statistician whose research has “influenced the theory and practice of statistics”. He was the founding chair of the Biostatistics Study Section (BMRD) at the National Institutes of Health. He is an elected Fellow of all three major international statistical organizations, and the AAAS. He has graduated 45 Ph.D. students.

David Hand (term ends 2018)

David Hand

David Hand

David Hand is Emeritus Professor of Mathematics at Imperial College, London, and Chief Scientific Advisor to Winton Capital Management. He is chair of the Research Board of the Data Science Institute at Imperial College. Previously he was professor and departmental chair of statistics at the Open University.

He received a BA in mathematics from Oxford University, and an MSc and PhD in statistics from Southampton University. He has served as President of the Royal Statistical Society (twice) and of the International Federation of Classification Societies. He is a non-executive director on the Board of the UK Statistics Authority, and chairs the UK’s Administrative Data Research Network. He is a fellow of the British Academy, the Institute of Mathematics and its Applications, and an Honorary Fellow of the Institute of Actuaries. He was awarded the Royal Statistical Society’s Guy Medal in Silver in 2002, and the Credit Collections and Risk Award for Contributions to the Credit Industry in 2012. He was made OBE for services to research and innovation in 2013.

David was the founding editor of Statistics and Computing and previously edited JRSS-A: Applied Statistics. He has published 300 scientific papers and 28 books, including Principles of Data Mining, Measurement Theory and Practice, The Improbability Principle, and The Wellbeing of Nations.

Sallie Keller (term ends 2019)

Sallie Keller

Sallie Keller, Ph.D., is professor of statistics and director of the Social and Decision Analytics Laboratory at the Biocomplexity Institute of Virginia Tech. Sallie’s prior positions were Academic Vice-President and Provost at University of Waterloo, director of the IDA Science and Technology Policy Institute, the William and Stephanie Sick Dean of Engineering at Rice University, head of the Statistical Sciences group at Los Alamos National Laboratory, professor of statistics at Kansas State University, and statistics program director at the National Science Foundation. Sallie has served as a member of the National Academy of Sciences Board on Mathematical Sciences and Their Applications, the Committee on National Statistics, and has chaired the Committee on Applied and Theoretical Statistics. Areas of expertise are social and decision informatics, statistical underpinnings of data science, uncertainty quantification, and data access and confidentiality. She is fellow of the American Association for the Advancement of Science, elected member of the International Statistics Institute, fellow and past president of the American Statistical Association, and member of the JASON advisory group. She holds a Ph.D. in statistics from the Iowa State University.

Rogemar Mamon (representative for the Fields Institute)

Rogemar Mamon

Rogemar Mamon

Rogemar Mamon is Professor in the Department of Statistical and Actuarial Sciences (SAS) at the University of Western Ontario. He served as Undergraduate Chair of SAS from 2008-11 and was Acting Associate Dean (Administration) in the Faculty of Science from 2014-15. His expertise spans the areas of applied probability, stochastic processes, actuarial science, and quantitative finance.

He worked previously in the insurance and banking sectors, as well as having held academic appointments at the University of Alberta and of Waterloo, at UBC, and at the Centre for the Analysis of Risk and Optimisation Modelling Applications at Brunel University in London, England, prior to joining Western. He also held short-term visiting appointments at the Isaac Newton Institute for Mathematical Sciences (Cambridge, England); Institute for Mathematics and Its Applications, University of Minnesota (USA); Maxwell Institute for Mathematical Sciences (Edinburgh, Scotland); University of Aarhus (Denmark); University of Calabria (Italy); University of Wollongong (New South Wales, Australia); University of Adelaide (Australia); and CIMAT (Guanajuato, Mexico).

His professional designations include Chartered Scientist, Science Council, UK; Chartered Mathematician, Institute of Mathematics and Its Applications (IMA), UK; and Fellow, Higher Education Academy, UK. He is also a Fellow of the IMA, and since 2009 he has been a co-editor of the IMA Journal of Management Mathematics published by Oxford University Press.

Together with his two co-authors, he was a recipient of the Society of Actuaries’ Prize for the Best Paper published in the North American Actuarial Journal in 2008. In 2013, he received a Research Grant Award from Italy’s Ministry of Education, Universities and Research under its “Messengers of Knowledge” programme, which involves the conduct of innovative and didactic research and teaching initiatives in the Convergence regions of Italy. The IMA bestowed upon him a Service Award in 2013 in recognition of his dedicated service and significant contribution to the Institute. He was named several times to the University Students’ Council Teaching Honour Roll for excellence in teaching at Western.

Michael Newton (term ends 2017)

Michael Newton

Michael Newton

Michael A. Newton is Professor at the University of Wisconsin Madison, in the Departments of Statistics and of Biostatistics and Medical Informatics, where he has worked since completing his PhD in Statistics at the University of Washington in 1991. His undergraduate training was in mathematics and statistics at Dalhousie University. Michael’s research concerns computational statistics, high-dimensional inference, and the development of statistics in the biological sciences. He has been fortunate to collaborate with others in multi-disciplinary projects. With a former PhD student, Michael reported the first application of Markov chain Monte Carlo in phylogenetic analysis (Mau & Newton, 1997, J. Comp. Graph. Stat.). He reported the first use of mixture models for analyzing high-dimensional gene expression changes (Newton et al., 2001, J. Comp. Bio.). His work has advanced statistical models in various domains, including: cancer-genomic aberrations (e.g. Newton, 2001, J. Amer. Stat. Assoc.); gene-function analysis (e.g. Wang and Newton, 2015, Ann. Appl. Stat.); RNA interference (e.g., Hao et al., 2013, PLoS Comp. Bio.); the biology of cancer initiation (e.g., Thliveris et al. 2005, PNAS). He has long been interested in Bayesian and empirical Bayesian computations, and recently resolved a general ranking problem in this domain (Henderson and Newton, 2015, J. Roy. Statist. Soc. B). He leads the biostatistics graduate training program at UW Madison and serves the field in various ways.

Douglas Nychka (representative for PIMS)

Doug Nychka

Doug Nychka

Douglas Nychka is a statistical scientist whose areas of research include the theory, computation and application of curve and surface fitting with a focus on geophysical and environmental applications. His current interests are in quantifying the uncertainty of numerical experiments that simulate the Earth’s present and possible future climate. His statistical expertise is in spline and spatial statistical methods especially as they are applied to large geophysical data sets and numerical models.

He has a Ph. D. in Statistics (1983) from the University of Wisconsin and he subsequently spent 14 years as a faculty member at North Carolina State University. He assumed leadership of the Geophysical Statistics Project (GSP) at the National Center for Atmospheric Research in 1997. GSP is a program funded by the National Science Foundation to develop collaborative research and training between statistics and the geosciences. In 2004, he became Director of the Institute of Mathematics Applied to Geosciences.

He has received the Jerry Sacks Award for Multidisciplinary Research (2004), the Distinguished Achievement Award Section on Statistics in the Environment (2013), and the Achievement Award for the International Statistics and Climatology Meeting (2013). He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.

Nancy Reid (Chair of the Scientific Advisory Committee)

Nancy Reid

Nancy Reid

Nancy Reid is the Director of CANSSI. She is University Professor and Canada Research Chair in Statistical Methodology at the University of Toronto. Her research interests are in statistical theory, likelihood inference, and design of studies. Along with her colleagues she has developed higher order asymptotic methods both for use in applications, and as a means to study theoretical aspects of the foundations of inference, including the interface between Bayesian and frequentist methods. She is interested in a number of substantive areas, including inference from large-scale surveys, environmental epidemiology, and high-energy physics.

She served on the scientific advisory panels of the National Program on Complex Data Structures, the Centre de Recherches Mathématiques, the Fields Institute for Research in the Mathematical Sciences, the Pacific Institute for Mathematical Sciences, and the Banff International Research Station. From 2010 through 2012 she chaired the steering committee for the Long Range Plan for Mathematical and Statistical Sciences Research in Canada, which was published in December 2012.

She is a past-president of the Statistical Society of Canada and the Institute of Mathematical Statistics (IMS), and a past member of NSERC Council. She is a Fellow of the RSC, AAAS, IMS, and the American Statistical Association. Her awards include the Krieger-Nelson prize of the Canadian Mathematical Society and the Gold Medal of the Statistical Society of Canada.

Christian P. Robert (term ends 2017)

Christian Robert

Christian P. Robert

Christian P. Robert received his Ph.D. degree in Mathematics in 1987 at the Université de Rouen, France. He became Full Professor in 1992 at Université de Rouen and finally joined the Department of Applied Mathematics at Université Paris-Dauphine in 2000. He became a senior member of the Institut Universitaire de France in 2010. He is part-time Professor at The University of Warwick since 2013. He was Head of the Statistics Laboratory at the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economics Studies (INSEE) from 1992 until 2010 and Adjunct Professor at École Polytechnique, France from 1992 until 2005.

Christian was co-editor of the Journal of the Royal Statistical Society, Series B, from 2006 until 2010, associate editor for the Annals of Statistics, Statistical Science and the Journal of American Statistical Association, etc. He is a fellow of the Institute of Mathematical Statistics, of the American Statistical Association, of the Royal Statistical Society, and a winner of the Young Statisticians Award of the Societé de Statistique de Paris in 1995. He was the president of the International Society for Bayesian Analysis (ISBA) in the year 2008 and has been a member of the councils of the above societies several times.

His research areas cover Bayesian statistics, with a focus on decision theory and model selection, numerical probability, with works cantering on the application of Markov chain theory to simulation, and computational statistics, developing and evaluating new methodologies for the analysis of statistical models. He has written over 150 research papers in these areas and their applications and he has supervised more than 20 Ph.D. students. He has also written or co‑written eight books on Bayesian statistics and computational methods. He was awarded the 2004 DeGroot prize for the second edition of his book ‘The Bayesian Choice’. His latest book is Introducing Monte Carlo Methods with R translated into French in 2011 (and soon to be translated into Japanese). He is currently completing the new editions of Bayesian Core with Jean-Michel Marin.

Nell Sedransk (term ends 2017)

Nell Sedransk

Nell Sedransk

Nell Sedransk received her PhD in Statistics from Iowa State University, Ames, Iowa. Currently she is Director of the National Institute of Statistical Sciences (NISS), Associate Director of Statistical and Applied Mathematical Sciences Institute (SAMSI) and Professor of Statistics at North Carolina State University. She is a member of Phi Beta Kappa, Phi Kappa Phi and also an Elected Member of the International Statistical Institute and Fellow of the American Statistical Association. Her career has carried her from academia where she taught and directed graduate students’ research to the federal government where she was Chief of Statistical Engineering for the National Institute of Standards and Technology, and then on to NISS and back into the academic setting to conduct and direct research in statistics and to mentor postdoctoral fellows and early career researchers. Her publications include co-authorship of four books and over a hundred primary research publications both in statistical theory and on notable advances in clinical medical research, engineering, and education.

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