Machine Learning and Public Health: Data Science Applications for Healthier Communities

  • November 13, 2020 from 12:00-1:00pm
  • Virtual Presentation through BlueJeans at
  • Please RSVP by emailing Lisa Maturo at
  • Please include your full name, email address, and institution/organization. 
  • We will provide instructions on obtaining CME credit for attendance.

In recent decades, there have been two significant technological advances that have fundamentally reshaped society: the development of extremely accurate predictive algorithms and the collection of vast quantities of data.  Taken together, the Machine Learning Revolution and Data Revolution have led to foundational shifts in all aspects of our society including public policy, urban planning, social media, climate science, and engineering.  Specifically in the field of public health, technological innovations have led to everything from computer vision-assisted diagnosis to wearable devices that monitor health conditions in real-time.  In this talk I will describe several projects that merge technological approaches with applications in the domain of public health.  These will include methodology for public greenspace usage assessment, computer vision-based quantification of point-of-sale tobacco advertising, and massive numerical simulations of COVID-19 spread throughout the state that are designed to measure policy impacts as well as aggregate behavioral characteristics of local populations.

Meet the Speaker

Gregory Dobler, PhD

Dr. Dobler is an Assistant Professor at the Biden School of Public Policy and Administration at the University of Delaware.  He is an urban data scientist whose research focuses on the study of dynamical interactions in complex urban systems.  As the Director of the multi-institutional Urban Observatory (UO) facility, he applies data analysis techniques from astronomy, computer vision, and machine learning to images of city skylines to study air quality, energy consumption, lighting technology, and sustainability.  He also leads data analysis projects on the equitable distribution of greenspaces, surrogate measures for traffic safety, and infectious disease spread.

This activity has been approved for AMA PRA Category 1 Credit

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