FDS Colloquium
FDS Women’s Career Development Colloquium Series: Cynthia Rush (Columbia)
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Speaker: Cynthia Rush (Columbia) Associate Professor of Statistics in the Department of Statistics at Columbia University Columbia University Friday, October 25, 2024 Lunch will be served in 1307; Meeting in 1327
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Please join us for the FDS Women’s Career Development Colloquium Series, proudly supported by the Department of Statistics and Data Science (S&DS) and the Yale Institute for Foundations of Data Science (FDS). This series will feature inspiring talks from female Yale alumni and leading professionals in statistics and related fields who will share their career journeys and valuable insights. We encourage active participation—ask questions, engage in discussions, and take full advantage of this enriching opportunity. The series is dedicated to supporting women in statistics and related fields at Yale, providing a platform where female professionals can share their experiences, discuss challenges, and offer guidance to our students.
Bio: Cynthia Rush is an Associate Professor of Statistics in the Department of Statistics at Columbia University. She earned her Ph.D. in Statistics from Yale University in May 2016, under the supervision of Andrew Barron. Prior to that, she completed her undergraduate studies at the University of North Carolina at Chapel Hill, where she received a B.S. in Mathematics.
Dr. Rush’s research focuses on the application of tools and concepts from information theory, statistical physics, and applied probability to address modern, high-dimensional inference and estimation problems. Her work tackles complex machine learning challenges in the fields of statistics and data science. A central theme of her research is exploring fundamental questions such as: How much data is needed to solve a complex statistical problem? How can data be effectively utilized to gain insight, and what are the limitations of this insight? Additionally, she is interested in developing and analyzing computationally efficient algorithms for statistical inference and estimation in these high-dimensional settings.
Organized by Ruixiao Wang, Ph.D. Student in Statistics & Data Science, Yale University
Please sign up asap to reserve your spot: https://forms.gle/NzjPhSau4H2VjpSW7
Connect with us on Slack: https://join.slack.com/t/women-in-stemgroup/shared_invite/zt-2ooxk8f8n-aU9kWy186Wnv8SSDo69R9A