Nov 16, 2017

CANSSI: Canadian Statistical Sciences Institute

Nancy Reid writes:

CANSSI is now in its third year of funding from the Natural Sciences and Engineering Research Council, and busy building for the future. The scientific flagship program continues to be the suite of Collaborative Research Team (CRT) projects, designed to build sustainable collaborations between statisticians and scientists.

To date we have supported nine CRT projects:

  • Advancements to State-Space Models for Fisheries Science
  • Copula Dependence Modeling: Theory and Applications
  • Statistical Modeling of the World: Computer and Physical Models in Earth, Ocean and Atmospheric Sciences
  • Evolved Marked Point Processes with Applications to Wildland Fire Regimes
  • Statistical Inference for Complex Surveys with Missing Observations
  • Modern Spectrum Methods in Time Series Analysis: Applications in Physical Science, Environmental Science and Computer Modeling
  • Joint Analysis of Neuroimaging Data: High-Dimensional Problems, Spatiotemporal Models and Computation
  • Rare DNA Variants and Human Complex Traits
  • Statistical Analysis of Administrative Health Databases

CANSSI provides partial funding for several workshops each year: in October 2016 the International Conference on Statistical Distributions and their Applications, jointly organized by CANSSI and the Department of Mathematics at Central Michigan University, welcomed 190 participants from 26 countries to Niagara Falls, Canada, including, of course, many IMS members.

We also have a program of post-doctoral fellowships, and provide funding for Canadian undergraduate students to attend the undergraduate research workshops at SAMSI. CANSSI leverages its funding by promoting thematic programs at Canada’s mathematical sciences institutes: there is an upcoming program, “Risk in complex systems: Models, applications, perceptions, and policy implications,” held at the Centre de Recherches Mathématiques in Montréal, August to December 2017.

CANSSI’s scientific activities are overseen by an international Scientific Advisory Committee: the members in 2017 are Raymond Carroll, David Hand, Sallie Keller, Rogemar Mamon, Michael Newton, Douglas Nychka, Christian Robert and Nell Sedransk. We are very grateful to them for their time and advice.

We continue to work on developing international linkages: we have close ties to SAMSI and NISS, and the Director of Norway’s Big Insight, Arnoldo Frigessi, is a member of our Board of Directors. We hope that there will soon be a national effort on data science in Canada, and that links between this and various organizations around the world will be a key component of the efforts of statistical sciences.

Our new Distinguished Visitor Program provides for special lectures by leading statistical scientists. The first DV was Peter Guttorp, who gave an evening talk at UBC–Okanagan in October 2016 on “Understanding the local impact of a warming planet.” In November 2016, Donald Rubin gave two wonderful lectures on causality and missing data at the Fields Institute as the CANSSI-supported Distinguished Lecture Series in Statistics. In 2017, Richard Cook of the University of Waterloo visited the University of Calgary, Hilary Parker of StitchFix visited McGill University and Philippe Soulier, Université Paris-Nanterre, visited the University of Ottawa.

We provide support to Canadian universities to participate in the ASA DataFest or other datathons, after great success with this at the University of Toronto in 2016. We also launched a small program to enable statistical scientists to “kick start” new collaborations with scientists. We have established a series of six Health Sciences Collaborating Centres across the country, to strengthen links with provincial and national health agencies, and highlight the many biostatistical training efforts with which our colleagues around the country are engaged.

Please don’t hesitate to contact me directly, reid@utstat.utoronto.ca, for further information about CANSSI, or to discuss how we might build linkages with you!

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