BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.4.0.1//EN TZID:America/New_York X-WR-TIMEZONE:America/New_York BEGIN:VEVENT UID:641@fds.yale.edu DTSTART;TZID=America/New_York:20241025T120000 DTEND;TZID=America/New_York:20241025T130000 DTSTAMP:20250916T142141Z URL:https://fds.yale.edu/events/fds-womens-career-development-colloquium-s eries-cynthia-rush-columbia/ SUMMARY:FDS Women's Career Development Colloquium Series: Cynthia Rush (Col umbia) DESCRIPTION:\nPlease join us for the FDS Women’s Career Development Collo quium 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 a nd leading professionals in statistics and related fields who will share t heir career journeys and valuable insights. We encourage active participat ion—ask questions\, engage in discussions\, and take full advantage of t his 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.\n\n\n\nBio: Cynthia Rush is an Associate Profes sor of Statistics in the Department of Statistics at Columbia University. She earned her Ph.D. in Statistics from Yale University in May 2016\, unde r the supervision of Andrew Barron. Prior to that\, she completed her unde rgraduate studies at the University of North Carolina at Chapel Hill\, whe re she received a B.S. in Mathematics.\n\n\n\nDr. Rush’s research focuse s on the application of tools and concepts from information theory\, stati stical physics\, and applied probability to address modern\, high-dimensio nal inference and estimation problems. Her work tackles complex machine le arning 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 ef fectively utilized to gain insight\, and what are the limitations of this insight? Additionally\, she is interested in developing and analyzing comp utationally efficient algorithms for statistical inference and estimation in these high-dimensional settings.\n\n\n\nOrganized by Ruixiao Wang\, Ph. D. Student in Statistics &\; Data Science\, Yale University\n\n\n\nPlea se sign up asap to reserve your spot: \;https://forms.gle/NzjPhSau4H2V jpSW7\n\n\n\nConnect with us on Slack: \;https://join.slack.com/t/wome n-in-stemgroup/shared_invite/zt-2ooxk8f8n-aU9kWy186Wnv8SSDo69R9A\n CATEGORIES:FDS Events,Colloquium,Student Led Seminar LOCATION:Yale Institute for Foundations of Data Science\, Kline Tower 13th Floor\, Room 1327\, New Haven\, CT\, 06511\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Kline Tower 13th Floor\, Ro om 1327\, New Haven\, CT\, 06511\, United States;X-APPLE-RADIUS=100;X-TITL E=Yale Institute for Foundations of Data Science:geo:0,0 END:VEVENT BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE END:VCALENDAR