The Constance van Eeden seminar is a yearly event in which graduate students from the University of British Columbia (UBC)’s Department of Statistics vote for their favourite statisticians. The winner is contacted by the organizing committee and invited to give a talk in the department’s seminar. The speaker spends one or two days on campus, and graduate students have the opportunity to have lunch and dinner with them.
CANSSI is proud to be a co-sponsor of this year’s event on April 4, 2024, with guest speaker Sherri Rose, Professor of Health Policy and Co-Director of the Health Policy Data Science Lab at Stanford University.
Attend the event online or in person:
Earth Sciences Building (ESB) 5104
2207 Main Mall
University of British Columbia
Vancouver, B.C.
There is no cost to participate.
REGISTER TO ATTEND THIS EVENT IN PERSON
REGISTER TO WATCH THIS EVENT ON ZOOM
What constitutes a fair algorithm and the ethical use of data is context specific. Algorithms are not neutral and optimization choices will reflect a specific value system and the distribution of power to make these decisions. Data also reflect societal bias, such as structural racism. Ethics and fairness research for health AI spans many fields, including policy, medicine, computer science, sociology, and statistics. Considerations go well beyond loss functions and typical measures of statistical assessment. This talk includes discussion of team construction, who decides the research question, minimum standards for research quality, reproducibility, least publishable units, and community engaged research. Overarching themes are also that centering health equity and developing methodology tailored to specific health questions are critical given the stakes involved.
Sherri Rose, Ph.D., is a Professor of Health Policy and Co-Director of the Health Policy Data Science Lab at Stanford University. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on risk adjustment, ethical algorithms in health care, comparative effectiveness research, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. In 2011, Dr. Rose coauthored the first book on machine learning for causal inference, with a sequel text released in 2018. Starting 2024, Dr. Rose will be co-teaching a new course at Stanford, Methods for Reproducible Population Health and Clinical Research.
Dr. Rose has been honoured with an NIH Director’s Pioneer Award, NIH Director’s New Innovator Award, the ISPOR Bernie J. O’Brien New Investigator Award, and multiple mid-career awards, including the Gertrude M. Cox Award. She was named a Fellow of the American Statistical Association in 2020 and received the 2021 Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics. Her research has been featured in The New York Times, USA Today, and The Boston Globe. She was Co-Editor-in-Chief of the journal Biostatistics from 2019 to 2023.
She received her Ph.D. in Biostatistics from the University of California, Berkeley, and a B.S. in Statistics from The George Washington University before completing an NSF Mathematical Sciences Postdoctoral Research Fellowship at Johns Hopkins University.
The van Eeden seminar is supported by the Constance van Eeden fund, which was established by Dr. van Eeden (1927–2021) in 1998. Dr. van Eeden was a mathematical statistician who made foundational contributions to estimation in restricted parameter spaces and nonparametric statistics.
The van Eeden fund is used to support many other activities on top of the student-invited speaker talk, such as inviting visiting professors for a week or more; organizing statistics summer schools; and giving out admissions awards to promising graduate students.
See the fund’s webpage to learn more!