Solving the Flint Water Crisis with Data Science


Eric Schwartz

Sunday, April 19th, 12-1pm PT / 3-4pm ET
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Solving the Flint Water Crisis with Data Science
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Join professor Eric Schwartz to discuss how cutting-edge machine learning is helping us solve water crises across the United States. Event Description: While lead in water is known to affect child development, what remains largely unknown is which homes are exposed to lead nationwide. In this fascinating talk with Eric Schwartz, we will explore how to reduce this unknown, starting with the Flint Water Crisis in Michigan. We’ll discuss the effectiveness of using cutting-edge machine learning methods to predict which homes in Flint likely have lead pipes. Born out of community-engaged research at the University of Michigan, this lead service line prediction approach is now being adopted across multiple states, in the private sector and in local and state government. Event Location: This event will take place online via Zoom, a free video-conferencing tool. New to Zoom? After you buy your ticket, you'll receive an email with step-by-step instructions on how to use it, and you'll be a pro in no time! Eric’s Bio: Eric Schwartz is an Assistant Professor of Marketing at the Stephen M. Ross School of Business at the University of Michigan. Professor Schwartz's expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively acquire customers and manage their relationships through interactive marketing experiments and adaptive data collection. His current projects aim to optimize firms' A/B testing and adaptive marketing experiments using a multi-armed bandit framework, often working with companies and organizations. Applying those same methods elsewhere, he also works on public policy problems focused on health and safety, including aiding local governments find and replace hazardous infrastructure, like lead pipes in Flint, Michigan. From that work he and his colleagues co-founded BlueConduit dedicated to removing lead pipes nationwide by applying machine learning. His work has been recognized with awards, including ISMS John D. C. Little Best Paper, Marketing Science Institute Young Scholar Award, AMA Young Quantitative Scholar Award, ISMS Doctoral Dissertation Proposal Competition Winner, and KDD Applied Data Science Best Student Paper. He is a member of the Editorial Review Board of INFORMS journal, Marketing Science. Before joining the Michigan Ross faculty in 2013, Professor Schwartz earned his Ph.D. in Marketing from the Wharton School and a B.A. in Mathematics and Hispanic Studies, all from the University of Pennsylvania. About Speakeasy: Speakeasy offers intimate events with compelling speakers and performers online via Zoom. Learn more about Speakeasy, and check out all of our events.

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