Meet Our People

Deputy Director
McGill University
andrea.benedetti@mcgill.ca

Andrea Benedetti is an Associate Professor, jointly appointed in the departments of Medicine and Epidemiology, Biostatistics & Occupational Health at McGill University.

She is primarily interested in the statistical challenges related to individual patient data meta-analysis. Andrea is a CIHR-funded biostatistician, and an author on more than 150 peer-reviewed publications.

She co-directs the DEPRESSD Project. This group has collected data from across the globe and used it to provide evidence-based information on the diagnostic accuracy of commonly-used depression screening tools. Andrea is supported by a Chercheur Boursier award from the FRQS.

Associate Director Representing Smaller Institutions
Trent University
wesleyburr@trentu.ca

Wesley Burr is is an Associate Professor of Statistics (and Chair of Department) in the Department of Mathematics at Trent University in Peterborough, Ontario.

Wesley received a BScEng in Mathematics and Engineering in 2005 from Queen’s University in Kingston, Ontario, and a PhD in Statistics in 2012 from the same institution, working under David J. Thomson. He was a postdoctoral fellow at Queen’s University from January to May 2013 and then held a Visiting Fellowship at Health Canada from June 2013 to March 2016.

His research focuses on problems at the intersection of time series analysis, spectrum estimation, and modelling, with current research focused on problems coming from environmental epidemiology. He is grateful for funding from both NSERC’s Discovery Grant program and federal agencies Health Canada, Agriculture and Agrifood Canada, and Natural Resources Canada.

Director
Simon Fraser University
donald_estep@sfu.ca

Donald Estep is the Director of CANSSI. He joined the Department of Statistics and Actuarial Science as Canadian Research Chair in Computational Probability and Uncertainty Quantification at Simon Fraser University. He moved from the Department of Statistics at Colorado State University, where he was Department Chair, University Distinguished Professor and University Interdisciplinary Research Scholar.

His research interests include uncertainty quantification for complex physics models, stochastic inverse problems, adaptive computation, and modeling of multiscale systems. Working with his collaborators, he has developed a systematic approach to a posteriori error estimation for simulations of complex systems, efficient numerical methods for uncertainty quantification for physical models, and theory and solution of inverse problems for stochastic parameters in physical models.

His application interests include ecology, materials science, detection of black holes, modeling of fusion reaction, analysis of nuclear fuels, hurricane wave forecasting, flow in porous media, and electromagnetic scattering. His research has been supported by multiple government agencies and national laboratories.

Don has served on several scientific advisory panels for the U.S. National Science Foundation and Department of Energy and on the Sandia National Laboratories CISE External Review Board and has co-authored several reports. He has served as the (founding) Chair of the SIAM Activity Group on Uncertainty Quantification, (founding) Co-Editor in Chief of the SIAM/ASA Journal on Uncertainty Quantification, and as SIAM representative to the Governing Board of SAMSI.

His awards include Fellow of the Society for Industrial and Applied Mathematics, the Computational and Mathematical Methods in Sciences and Engineering (CMMSE) Prize, and the Chalmers Jubilee Professorship of Chalmers University of Technology.

Associate Director Representing Prairies
University of Manitoba
M_Jafari_Jozani@umanitoba.ca

Mohammad Jafari Jozani is currently an Associate Professor with the Department of Statistics and an adjunct professor of Biomedical Engineering at the University of Manitoba in Winnipeg.

His current research involves statistical learning problems with high dimensional aspects in biostatistics, engineering and sustainable energy; small area estimation as well as statistical inference with complex sampling designs using order statistics and rank information. The focal point of his research program is on developing new methodologies, models and computational tools to solve data driven problems in a variety of application domains.

He has applied his research in areas such as breast cancer studies, BMD analysis and osteoporosis, mercury contamination in fish bodies, and recently in the calibration problems to design simulators for training purposes in order to make surgeries safer.

Associate Director Representing Ontario
University of Toronto
lisa.strug@utoronto.ca

Lisa J. Strug is a Senior Scientist at the Research Institute of The Hospital for Sick Children and is an Associate Professor in the Department of Statistical Sciences and the Division of Biostatistics at the University of Toronto.

She is the Associate Director of The Centre for Applied Genomics, a federally funded Toronto-based genome centre and one of three centres contributing to a national platform providing genome sequencing and analysis services in Canada and Internationally.  Her research has focused on statistical genetics and genomics, on the foundations of statistics and on their intersection.

She is the associate editor and statistical genetics editor of npj Genomic Medicine and is the Tier 1 Canada Research Chair in Genome Data Sciences.

Associate Director Representing Quebec
Université Laval
denis.talbot@fmed.ulaval.ca

Denis Talbot is a professor in the Department of Social and Preventive Medicine at Université Laval. He participated in the creation of the graduate programs in biostatistics there. He was elected as a regional representative for Quebec at the Statistical Society of Canada (SSC) in 2021 for a two-year term and is also a member of the bilingualism committee and the membership committee of the SSC.

His research interests concern causal inference methods for the analysis of observational data. He is also doing collaborative work in various areas including psychosocial stressors at work, vaccine effectiveness, cardiovascular health, and cancer. His program of research has been supported by grants from NSERC, CIHR and by research-career awards from the Fonds de recherche du Québec – Santé.

Associate Director Representing Alberta, British Columbia, Yukon
University of British Columbia
lang@stat.ubc.ca

Lang Wu is a Professor in the Department of Statistics at the University of British Columbia in Vancouver. He holds a PhD in Statistics from the University of Washington in Seattle.

His research has focused on analysis of longitudinal data based on mixed effects models, joint modelling longitudinal and survival data, missing data and measurement errors, and order-restricted hypothesis testing. He has applied his research in HIV/AIDS studies, cancer studies, and other health-related areas.

Associate Director Representing Atlantic Canada
Memorial University of Newfoundland
yyilmaz@mun.ca

Yildiz Yilmaz is an Associate Professor and Deputy Head, Statistics, in the Department of Mathematics and Statistics at Memorial University in St. John’s, Newfoundland and Labrador. She joined the department in 2013 after completing her PhD at the University of Waterloo in 2009 and working as a postdoctoral fellow at the Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital and the Dalla Lana School of Public Health, University of Toronto, between 2009 and 2013.

Her research interests are in the areas of statistical theory and methodology, and in statistical methods in biostatistics and statistical genetics. In particular, her work focuses on survival analysis, event history analysis, multivariate modeling and analysis, causal inference, incomplete data analysis and response-selective sampling. Her work has been motivated by important problems in biomedicine and genetics.

She currently has the following research programs within the field of statistics, genetic epidemiology and statistical genetics: (1) development and application of novel methods to model time-to-event phenotypes in genome-wide prognosis studies; (2) development and application of novel genetic association methods based on joint models and directional models of multiple phenotypes; (3) evaluation of designs and statistical methods under response-dependent sampling; and (4) development of methods to model multivariate survival times.

Term ends: December 2024

Scarlett Bellamy joined the Boston University (BU) School of Public Health community as Chair and Professor of Biostatistics on July 1, 2023.

Prior to her arrival at BU she was a professor in the Department of Epidemiology and Biostatistics and the Associate Dean for Diversity and Inclusion at Drexel University Dornsife School of Public Health. Before joining Drexel University in 2016, Bellamy spent 15 years at the University of Pennsylvania (UPenn) Perelman School of Medicine, where she was a professor of biostatistics. She holds a bachelor’s degree in mathematics from Hampton University and completed her doctoral training in biostatistics at the Harvard University T.H. Chan School of Public Health.

Much of Bellamy’s research centres on evaluating the efficacy of interventions in longitudinal behavioural modification trials, including cluster- and group-randomized trials. She is particularly interested in applying this methodology to address health disparities for a variety of clinical and behavioural outcomes, including HIV/AIDS, cardiovascular disease, and health-promoting behaviours.

Bellamy previously served as the co-principal investigator of the Data Coordinating Center for the Prematurity and Respiratory Outcomes Program at UPenn, which aimed to improve respiratory outcomes during the first year of life after preterm birth. She was also PI of the Fostering Diversity in Biostatistics Workshop at the Eastern North American Region of the International Biometric Society (ENAR). This federally funded initiative aims to increase the number of underrepresented minorities in graduate training and professional careers in biostatistics.

In 2016, Bellamy was elected a fellow of the American Statistical Association (ASA). The designation has been an honour for nearly 100 years, and under ASA bylaws, only one-third of one percent of the total association membership may be elected as fellows each year.

In 2017, Bellamy served as the president of ENAR. She also currently serves as a statistical collaborator for the Center for Health Equity Research and Promotion at the Corporal Michael J. Crescenz Veterans Affairs Medical Center in Philadelphia.

Term ends: December 2025

Jay Breidt is a Senior Fellow in the Department of Statistics and Data Science at NORC at the University of Chicago. He is also Professor Emeritus and past Chair of the Department of Statistics at Colorado State University. His expertise is mathematical statistics, with interests that include survey sampling, time series, nonparametric regression, and uncertainty quantification for complex scientific models.

Breidt received his PhD at Colorado State University in 1991 and spent the first nine years of his career at Iowa State University as an assistant professor and tenured associate professor, before returning to Colorado State in 2000.

Breidt has an extensive record of refereed publications. He has presented over 130 invited short courses, conference talks, and academic seminars. Breidt has been an associate editor for seven different journals and Reviews Editor for the Journal of the American Statistical Association and The American Statistician. He has served on six review committees for the National Academy of Sciences. He is past Chair of the American Statistical Association National Committee on Energy Statistics (an advisory panel for the Energy Information Administration, US Department of Energy), has served two terms on the Federal Economic Statistics Advisory Committee, and currently chairs the Census Scientific Advisory Committee for the US Census Bureau.

Breidt has received numerous honors, including recognition with a national prize in environmental statistics, elected membership in the International Statistical Institute, and elected fellowship in both the American Statistical Association and the Institute of Mathematical Statistics.

Term ends: December 2025

Peter Craigmile is a Professor in the Department of Mathematics and Statistics at Hunter College, The City University of New York (CUNY). He also serves as an Honorary Research Fellow in the School of Mathematics and Statistics, University of Glasgow, Scotland. He was previously a Professor in the Department of Statistics at The Ohio State University.

His research interests include time series analysis, spatial statistics, space-time modeling, and longitudinal methods. He is interested in the use of spectral and wavelet methods to investigate dependency structures and to analyze periodicities and trends. One application of this is to the study of long memory processes. In collaboration with others, he has developed methods for spatial exceedances and extremes, which are critical to assessing spatially varying risk of environmental change or disease. He enjoys application-oriented research in areas such as Biology, Climatology, Environmental Sciences, Public Health, and Psychology.

Professor Craigmile is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and The Royal Statistical Society.

Term ends: December 2024

Aurore Delaigle is a Professor and ARC Future Fellow at The University of Melbourne. Before moving to Melbourne in 2007, she held positions at the University of of California at Davis and at San Diego, and at the University of Bristol.

Aurore’s main research interests include nonparametric estimation, measurement errors, deconvolution problems and functional data analysis. She is particularly interested in developing new methods for indirectly and imperfectly observed data, especially if they have some seemingly unappealing form (e.g., incomplete, irregular, non-stationary, too big to handle with usual methods).

In 2013, Aurore was elected a Fellow of the Institute of Mathematical Statistics (IMS) and was awarded the Moran Medal from the Australian Academy of Science.

In 2018 she became a Fellow of the American Statistical Association and in 2020 she was elected Fellow of the Australian Academy of Science.

Term ends: December 2026

Sandrine Dudoit is Associate Dean for the Faculty and Research in the College of Computing, Data Science, and Society, Professor in the Department of Statistics, and Professor in the Division of Biostatistics, School of Public Health, at the University of California (UC), Berkeley. She was Chair of the Department of Statistics at UC Berkeley from July 2019 to June 2022. Professor Dudoit’s methodological research interests regard high-dimensional statistical learning and include exploratory data analysis (EDA), visualization, loss-based estimation with cross-validation (e.g., density estimation, classification, regression, model selection), and multiple hypothesis testing. Much of her methodological work is motivated by statistical questions arising in biological research and, in particular, the design and analysis of high-throughput sequencing studies, e.g., single-cell transcriptome sequencing (RNA-Seq) for discovering novel cell types and for the study of stem cell differentiation. Her contributions include: exploratory data analysis, normalization and expression quantitation, differential expression analysis, class discovery and prediction, inference of cell lineages, and the integration of biological annotation metadata (e.g., Gene Ontology (GO) annotation). She is also interested in statistical computing and, in particular, computationally reproducible research. She is a founding core developer of the Bioconductor Project, an open-source and open-development software project for the analysis of biomedical and genomic data.

Professor Dudoit is a co-author of the book Multiple Testing Procedures with Applications to Genomics and a co-editor of the book Bioinformatics and Computational Biology Solutions Using R and Bioconductor. She is Associate Editor of three journals, including The Annals of Applied Statistics and IEEE/ACM Transactions on Computational Biology and Bioinformatics. Professor Dudoit was named Fellow of the American Statistical Association (2010), Elected Member of the International Statistical Institute (2014), and Fellow of the Institute of Mathematical Statistics (2021).

Professor Dudoit obtained a Bachelor’s degree (1992) and a Master’s degree (1994) in Mathematics from Carleton University, Ottawa, Canada. She first came to UC Berkeley as a graduate student and earned a PhD degree in 1999 from the Department of Statistics. Her doctoral research, under the supervision of Professor Terence P. Speed, concerned the linkage analysis of complex human traits. From 1999 to 2000, she was a postdoctoral fellow at the Mathematical Sciences Research Institute, Berkeley. Before joining the Faculty at UC Berkeley in July 2001, she underwent two years of postdoctoral training in genomics in the laboratory of Professor Patrick O. Brown, Department of Biochemistry, Stanford University. Her work in the Brown Lab involved the development and application of statistical methods and software for the analysis of microarray gene expression data.

Committee Chair

Donald Estep is the Director of CANSSI. He joined the Department of Statistics and Actuarial Science as Canadian Research Chair in Computational Probability and Uncertainty Quantification at Simon Fraser University. He moved from the Department of Statistics at Colorado State University, where he was Department Chair, University Distinguished Professor and University Interdisciplinary Research Scholar.

His research interests include uncertainty quantification for complex physics models, stochastic inverse problems, adaptive computation, and modeling of multiscale systems. Working with his collaborators, he has developed a systematic approach to a posteriori error estimation for simulations of complex systems, efficient numerical methods for uncertainty quantification for physical models, and theory and solution of inverse problems for stochastic parameters in physical models.

His application interests include ecology, materials science, detection of black holes, modeling of fusion reaction, analysis of nuclear fuels, hurricane wave forecasting, flow in porous media, and electromagnetic scattering. His research has been supported by multiple government agencies and national laboratories.

Don has served on several scientific advisory panels for the U.S. National Science Foundation and Department of Energy and on the Sandia National Laboratories CISE External Review Board and has co-authored several reports. He has served as the (founding) Chair of the SIAM Activity Group on Uncertainty Quantification, (founding) Co-Editor in Chief of the SIAM/ASA Journal on Uncertainty Quantification, and as SIAM representative to the Governing Board of SAMSI.

His awards include Fellow of the Society for Industrial and Applied Mathematics, the Computational and Mathematical Methods in Sciences and Engineering (CMMSE) Prize, and the Chalmers Jubilee Professorship of Chalmers University of Technology.

Term ends: December 2025

Kerrie Mengersen holds a BA (Hons) in Mathematical Statistics and Computing and a PhD in Mathematical Statistics, both from the University of New England, New South Wales, Australia. She has held positions as a commercial statistical consultant and an academic staff member at four Australian universities. She is currently a Distinguished Research Professor in Statistical Science and the Director of the QUT Centre for Data Science at Queensland University of Technology and holds a concurrent role as Associate Member in the Department of Statistics at the University of Oxford, UK. She was a Deputy Director in the ARC Centre of Excellence in Mathematical and Statistical Frontiers (2015–2021) and an ARC Laureate Fellow (2015–2021). In 2018 she was elected as a Fellow of the Australian Academy of Science (AAS), the Academy of Social Sciences in Australia (ASSA) and the Queensland Academy of Arts and Sciences (QAAS). She is an active member of the Institute for Mathematical Sciences, International Biometrics Society, International Statistical Institute and the Statistical Society of Australia.

Distinguished Professor Mengersen focuses on using and developing new statistical and computational methods that can help to solve complex problems in the real world. These problems are in the fields of environment, genetics, health and medicine, and industry. She enjoys working with a diverse range of people doing outstanding things in many different areas, and contributing expertise in an important component of their work. Her research interests include:

• Complex systems modelling
• Bayesian statistical modelling, computational methods and applications
• Bayesian networks
• Applied statistics.

Term ends: December 2026

J. Sunil Rao has been Professor in the Division of Biostatistics at the University of Minnesota and Director of Biostatistics at the University of Minnesota Masonic Comprehensive Cancer Center since January 1, 2023. From 2010 to 2022, he was the Director of the Division of Biostatistics in the Department of Public Health Sciences at the University of Miami, Miller School of Medicine. From June 2016 to December 2019, he was the Interim Chair of the Department of Public Health Sciences.

From 1998 to 2010, he was in the Department of Epidemiology and Biostatistics at Case Western Reserve University School of Medicine, where he rose to Full Professor. For the last five of those years, he was Director of the Division of Biostatistics. From 1994 to 1998, he was on faculty in the Department of Biostatistics at the Cleveland Clinic Foundation.

He graduated from the University of Toronto in 1994 with a PhD in Biostatistics under the guidance of Rob Tibshirani. In 1991, he received an MS degree in Biostatistics from the University of Minnesota, and in 1989 he received a BSc from the University of Ottawa with a double major in Biology and Biochemistry. He is a Fellow of the American Statistical Association (2011), Elected Member of the International Statistical Institute (2016), a Fellow of the Institute of Mathematical Statistics (2024), and an Honorary Member of the Society of Statistics, Computer and Applications (2024).

Term ends: December 2025

Jessica Utts is a Professor Emerita in the Department of Statistics at University of California, Irvine, and was the 2016 President of the American Statistical Association (ASA). She has a long-standing interest in promoting statistical literacy, and has published three statistics textbooks with that emphasis. She is a Fellow of the ASA, the Institute of Mathematical Statistics, the American Association for the Advancement of Science, and the Association for Psychological Science. She is the recipient of numerous awards, including the George Cobb Lifetime Achievement Award in Statistics Education, the Samuel S. Wilks, Memorial Award,  the ASA Founder’s Award, the IMS Harry C. Carver Medal, the National Institute of Statistical Sciences (NISS) Distinguished Service Award, and two campus-wide awards for distinguished teaching. She has served as President of the Western North American Region of the International Biometric Society, Chair of the Committee of Presidents of Statistical Societies (COPSS), Vice-Chair of the NISS Board, and a member of the Council of the International Statistical Institute. In addition to statistics education her research involves applications of statistics to a variety of areas, most notably parapsychology, for which she has appeared on TV shows including Larry King Live, Nightline and CNN News. Her most recent work is on incorporating ethics into data science education.

Term ends: December 2026

Dr. Alyson Wilson is the Senior Associate Vice Chancellor for Research at North Carolina State University. She is also a professor in the Department of Statistics and Principal Investigator for the Laboratory for Analytic Sciences. She is a Fellow of the American Statistical Association and the American Association for the Advancement of Science. Her research interests include statistical reliability, Bayesian methods, and the application of statistics to problems in defense and national security.

Prior to joining NC State, Dr. Wilson was a jointly appointed research staff member at the IDA Science and Technology Policy Institute and Systems and Analyses Center (2011–2013); associate professor in the Department of Statistics at Iowa State University (2008–2011); Scientist 5 and technical lead for Department of Defense Programs in the Statistical Sciences Group at Los Alamos National Laboratory (1999–2008); and senior statistician and operations research analyst with Cowboy Programming Resources (1995–1999).

Dr. Wilson is currently serving on the National Academy of Sciences Committee on Applied and Theoretical Statistics and as Chair of the Board of Trustees for the National Institute of Statistical Sciences. She is an elected member of the International Statistical Institute and a member of the NC State Research Leadership Academy. She is the former Reviews Editor for the Journal of the American Statistical Association and the American Statistician and a founder and past-chair of the American Statistical Association’s Section on Statistics in Defense and National Security.

2023

• Scarlett Bellamy, Drexel University (Jan 2022–Dec 2024)
• Jay Breidt, University of Chicago (Jan 2023–Dec 2025)
• Peter Craigmile, Hunter College, City University of New York (Jan 2023–Dec 2025)
• Corina Constantinescu, University of Liverpool (Jan 2021–Dec 2023)
• Aurore Delaigle, University of Melbourne (Jan 2022–Dec 2024)
• Josée Dupuis, McGill University (Jan 2021–Dec 2023)
• Donald Estep, CANSSI & Simon Fraser University (Jul 2019– )
• Sujit Ghosh, North Carolina State University (Jan 2021–Dec 2023)
• Kerrie Mengersen, Queensland University of Technology (Jan 2023–Dec 2025)
• Jessica Utts, University of California, Irvine (Jan 2023–Dec 2025)

2022

• Scarlett Bellamy, Drexel University (Jan 2022–Dec 2024)
• Daniela Calvetti, Case Western Reserve University (Jan 2020–Dec 2022)
• Merlise Clyde, Duke University (Jan 2020–Dec 2022)
• Corina Constantinescu, University of Liverpool (Jan 2021–Dec 2023)
• Aurore Delaigle, University of Melbourne (Jan 2022–Dec 2024)
• Josée Dupuis, McGill University (Jan 2021–Dec 2023)
• Donald Estep, CANSSI & Simon Fraser University (Jul 2019– )
• Sujit Ghosh, North Carolina State University (Jan 2021–Dec 2023)
• Naisyin Wang, University of Michigan (Jan 2020–Dec 2022)
• Bin Yu, University of California, Berkeley (Jan 2021–Dec 2022)

2021

• Amy Braverman, Jet Propulsion Laboratory, NASA (Jan 2019–Dec 2021)
• Daniela Calvetti, Case Western Reserve University (Jan 2020–Dec 2022)
• Merlise Clyde, Duke University (Jan 2020–Dec 2022)
• Corina Constantinescu, University of Liverpool (Jan 2021–Dec 2023)
• Josée Dupuis, McGill University (Jan 2021–Dec 2023)
• Donald Estep, CANSSI & Simon Fraser University (Jul 2019– )
• Sujit Ghosh, North Carolina State University (Jan 2021–Dec 2023)
• Marina Vannucci, Rice University (Jan 2019–Dec 2021)
• Naisyin Wang, University of Michigan (Jan 2020–Dec 2022)
• Bin Yu, University of California, Berkeley (Jan 2021–Dec 2023)

2020

• Amy Braverman, Jet Propulsion Laboratory, NASA (Jan 2019–Dec 2021)
• Daniela Calvetti, Case Western Reserve University (Jan 2020–Dec 2022)
• Merlise Clyde, Duke University (Jan 2020–Dec 2022)
• Donald Estep, CANSSI & Simon Fraser University (Jul 2019– )
• Yulia Gel, University of Texas at Dallas (Jan 2018–Dec 2020)
• Xuming He, University of Michigan (Jan 2018–Dec 2020)
• Doug Nychka, Colorado School of Mines (Oct 2015–Dec 2020)
• David Stephens, McGill University (Apr 2016–Dec 2020)
• Marina Vannucci, Rice University (Jan 2019–Dec 2021)
• Naisyin Wang, University of Michigan (Jan 2020–Dec 2022)