Great Problems, Great Minds Seminar, Urban Health Risk Mapping: Predicting and Mapping Neighborhood-Scale Health Outcomes

Join the Department of Social Sciences for this Great Problems, Great Minds seminar featuring Junfeng Jiao, who will discuss his research involving a machine learning system that can measure the health effects of neighborhood environments in ten major U.S. cities using public data. The event will take place on April 1 from 12:40-1:40 p.m.

Bio

Junfeng Jiao, an associate professor and director of the Urban Information Lab at the University of Texas at Austin, will discuss his research involving a machine learning system that can measure the health effects of neighborhood environments in ten major U.S. cities using public data. This system provides insight into the relationship between different health outcomes (e.g. obesity, stroke, cancer, diabetes, etc.) and surrounding build environments at the census tract level. There is also an interactive website that allows users to understand how changes to their neighborhoods can affect their health; for example, if a user changes neighborhood sidewalk density, the website will show the expected changes in health behavior and outcomes, such as decreased physical activity level and increased diabetes risk.

Click here to join the event on April 1.

The event is part of the Great Problems, Great Minds seminar series which explores the major problems facing humanity as we move into the heart of the 21st century. To see the full schedule and videos from previous events, visit the seminar series page.