Explore emerging work applying machine learning in research on how laws influence health and well-being.
Klaus Mueller is a professor of computer science at Stony Brook University where he specializes in using machine learning to create visualization systems that make complex information accessible to stakeholders. Professor Mueller’s work brings machine learning theory and methods to support legal epidemiology, the scientific study of the health effects of laws and legal practices, representing an opportunity to bridge the science behind machine learning with the work of conventional causal inference research. It is a cutting-edge approach to both identifying laws that work through research and to using data visualizations and user dashboards to help spread the word about policy change beneficial to health and well-being. The presentation is of interest in law, health, computer science and anyone interested in positive change.
Klaus Mueller, PhD, Professor, Director Visual Analytics and Imaging Lab, Center for Visual Computing, Stony Brook University (bio)
Commenter: Pricila Mullachery, PhD MPH, Assistant Professor, Dept. of Health Services Administration and Policy, College of Public Health; Faculty Fellow, Center for Public Health Law Research (bio)
Moderator: Scott Burris, JD, Professor and Director, Center for Public Health Law Research, Temple University Beasley School of Law and College of Public Health
This event is sponsored by the Center for Public Health Law Research, the Institute for Law, Innovation & Technology, and the Health Law Society at the Temple University Beasley School of Law, as well as the CST Data Analytics Center and the Temple University College of Public Health. Additional support was provided by the Temple University Faculty Senate Lectures and Forums Committee.