Picture a Scientist

woman holding up device in lab

Event Registration Page

CANSSI is hosting a virtual screening of the film Picture a Scientist, followed by a live, virtual panel discussion.

Picture a Scientist is a feature-length documentary film chronicling the groundswell of researchers who are writing a new chapter for women scientists. A biologist, a chemist and a geologist lead viewers on a journey deep into their own experiences in the sciences, overcoming brutal harassment, institutional discrimination, and years of subtle slights to revolutionize the culture of science. From cramped laboratories to spectacular field stations, we also encounter scientific luminaries who provide new perspectives on how to make science itself more diverse, equitable, and open to all.

Film Screening – Picture a ScientistMay 14-16, 2021Watch the film any time during this timeframe.
Live Online Panel DiscussionMay 18, 202114:00-15:15 EDT
11:00-12:15 PDT

Watch the Film

Register now and we will send you a link and password to watch the film. You will have access to this film from May 14-16. You can pause and return to view or watch it again. The platform allows for an unlimited number of views during that timeframe.

Registration closes on May 11, 2021.

Register for the Panel Discussion

The goal of the panel is to expose and discuss the issues of equity, diversity and inclusion (EDI) raised in “Picture a Scientist” in the specific context of academic statistical sciences in Canada. The panelists will bring their personal experiences in dealing with EDI issues in Canadian universities to the panel discussion. 

This virtual panel will take place on Tuesday, May 18 from 14:00-15:15 EDT (11:00-12:15 PDT)

When you register to watch the film, you are automatically registered for the panel session as well.

About the Panelists

Claudie Beaulieu is a climate statistician and Assistant Professor in the Ocean Sciences Department at the University of California Santa Cruz, and leads the Ocean and Climate Data Science lab at UCSC. She received a BSc in Statistics from Université Laval, a PhD in Water Sciences from INRS-ETE and she conducted postdoctoral research at Princeton University in the Atmospheric and Oceanic Sciences Program. She was a Lecturer at the University of Southampton in the UK before moving to UCSC. Her research focuses on quantifying ocean & climate variability and change through advanced statistical approaches. Throughout her career she received multiple awards and distinctions for her work, including a FQRNT excellence prize for the “Most distinguished 2009 PhD thesis in natural sciences and engineering in Quebec”.

Laura Cowen is the Associate Dean Research and an Associate Professor of Statistics in the Faculty of Science at the University of Victoria. Trained as a field biologist, she did extensive remote field research on seabirds in British Columbia and Alaska. Laura obtained her MMath in Biostatistics from the University of Waterloo and PhD in Statistics from Simon Fraser University with a focus on ecological statistics, primarily working on mark-recapture models. She is PI on a CANSSI CRT grant developing methods for integrated ecological models. Laura is the current President of WNAR and a member of CANSSI’s IDEA planning committee. As an ecological statistician, her collaborative research has spanned both ecology and health, studying injection drug users, syphilis, seabirds, rock lobsters, and fish – anything hiding that needs counting. Laura is currently coping with the pandemic by walking laps of her neighbourhood and estimating hidden COVID-19 cases with a multi-institutional group of mathematicians, statisticians, and health researchers, while trying to keep her cat off her keyboard and kids out of her Zoom meetings.

Marie-Hélène Roy-Gagnon is an Associate Professor at the School of Epidemiology and Public Health at the University of Ottawa. She completed her PhD in Genetic Epidemiology at the Johns Hopkins University Bloomberg School of Public Health, followed by postdoctoral fellowships at NIH and the University of Michigan. She also holds an MSc in statistics from the Université Laval. Her main research interests lie in the development and optimal use of statistical and epidemiological methods to study genetic factors involved in the etiology of health-related traits. Marie-Hélène’s methodological work is performed in the context of multidisciplinary collaborations, with current projects including studies on cardiovascular disease and obesity, orofacial clefts and asthma.

Jamie Stafford is a Professor at the Department of Statistical Sciences at the University of Toronto and is also a Provostial Advisor for Data Science at the University. He has held Visiting Professor positions at the University of Chicago, Stanford University and École Polytechnique Fédérale de Lausanne. He is a recipient of the Premier’s Research Excellence Award and recently received the Distinguished Service Award from the Statistical Society of Canada for his enthusiastic and dynamic leadership in statistical science across Canada — including serving as the Director of the National Program on Complex Data Structures. His research focus is in asymptotics, symbolic computation and spatio-temporal methods. He recently developed a research program in spatial data analysis with a special emphasis on local smoothing methods applied to non-standard and complex data.

Grace Y. Yi is a Professor of the Department Statistical and Actuarial Sciences and the Department of Computer Science at the University of Western Ontario where she currently holds a Tier I Canada Research Chair in Data Science. Grace received her PhD in Statistics from the University of Toronto in 2000. She is a Fellow of the Institute of Mathematical Statistics, Fellow of the American Statistical Association, and an Elected Member of the International Statistical Institute. In 2010, Grace received the Centre de recherches mathmatiques and the Statistical Society of Canada (CRM-SSC) Prize. She was a recipient of the University Faculty Award (2004-2009) granted by the Natural Sciences and Engineering Research Council of Canada. Grace was the Editor-in-Chief of The Canadian Journal of Statistics (2016-2018). She now acts as the Editor of the Statistical Methodology section for the Journal of New England of Statistics in Data Science. Grace was President of the Biostatistics Section of the Statistical Society of Canada in 2016, and the Founder of the first chapter (Canada Chapter, established in 2012) of International Chinese Statistical Association. She is currently President Elect of the Statistical Society of Canada.

About the Moderator

Aurélie Labbe is an Associate Professor at HEC Montréal in the Department of Decision Sciences and holds the FRQ-IVADO research chair in Data Science. After receiving her PhD in 2005, Aurélie was hired as an Associate Professor in the Université Laval’s Math and Statistics Department, where she taught until 2009. In 2009, she joined the Department of Epidemiology and Biostatistics and the Department of Psychiatry at McGill University, where she was first an Assistant Professor, then an Associate Professor until 2016. She has developed her research portfolio as a lead researcher on several projects funded in part by the Natural Sciences and Engineering Research Council (NSERC) and the Canadian Institutes of Health Research (CIHR) with the goal of developing statistical tools for analysing genetic data. These tools have further applications in neuroscience. In 2016, Aurélie joined the Department of Decision Sciences at HEC Montréal as an associate professor and member of the Canada Excellence Research Chair in Data Science for Real-time Decision Making. She has since branched out to other fields of data science, focusing on the analytical challenges generated by data from intelligent transportation systems.

About CANSSI’s Commitment to Equity, Diversity, and Inclusion

The creation of an equitable, diverse and inclusive Canadian statistics and inferential data science research enterprise is necessary for CANSSI to achieve its mission and for the statistical and inferential data science community to respond effectively to local, national and global challenges.

Learn more about CANSSI’s commitment to EDI. 

This event is a part of CANSSI’s EDI program.

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