04-18, 10:55–11:30 (US/Eastern), Auditorium 3
When every day counted during the COVID-19 pandemic, data science became an essential catalyst in accelerating the path to widespread vaccination. This talk delves into the data-driven strategies that enabled the U.S. government’s vaccine trials to move faster, cutting crucial weeks—6 to 8, by our estimates—off the timeline to deployment. Through sophisticated geospatial modeling, we identified and swiftly mobilized trial recruitment efforts in emerging hot zones, ensuring that each candidate pool was both numerically sufficient and demographically representative. Attendees will discover how advanced analytics, predictive modeling, and interdisciplinary collaboration converged to target the right communities at the right time, ultimately expediting vaccine availability. This behind-the-scenes look at rapid-response data science highlights not just the technical innovations, but the decisive cultural and operational shifts that turned real-time insights into life-saving action.
This talk explores how data science accelerated COVID-19 vaccine trials, saving 6-8 weeks in deployment. Through geospatial modeling, we targeted diverse recruitment in emerging hot zones, ensuring efficient and representative trials. Attendees will discover how advanced analytics and collaboration turned insights into life-saving action.
Previous knowledge expected
Greg Michaelson is Cofounder and Chief Product Officer at Zerve, a young, stealthy startup that’s rethinking the data science development experience. Previously, Greg was an early joiner at DataRobot where he played many roles, including Chief Customer Officer. Prior to that, he worked as a data scientist in the financial sector after earning a PhD in applied statistics from the University of Alabama. In his spare time, Greg manufactures a line of flavored breakfast cereal toppings called Cerup. He lives in Spring Creek, Nevada with his wife, four children, and two Clumber Spaniels.