Speaker's Profile

Kasey Claborn is the Director of the Addiction Research Institute housed within the Steve Hicks School of Social Work at UT Austin. A research scientist and licensed clinical psychologist, Dr. Claborn serves as an assistant professor in the Steve Hicks School of Social Work and the Department of Psychiatry at Dell Medical School, and an adjunct assistant professor of medicine at The Warren Alpert Medical School of Brown University and serves as Co-Director for the South Southwest Addiction Technology Transfer Center.Dr. Claborn received her Ph.D. in clinical psychology from Oklahoma State University and completed her internship at the University of Florida Health Sciences Center. She completed her postdoctoral fellowship at Brown University’s Center for Alcohol and Addiction Studies, where she crossed-trained in HIV and addictive behaviors at the Alcohol Research Center on HIV. Prior to joining the University of Texas, Dr. Claborn served as an Assistant Professor (research) in psychiatry and human behavior at Brown University. Dr. Claborn has been the Principal Investigator for several projects funded by the National Institutes of Health, the Substance Abuse and Mental Health Services Administration, and the Health Resources and Services Administration. To date, she has received over $12 million dollars in external funding for her research. Dr. Claborn’s research focuses on improving the addiction system of care through community based participatory research methods and system science. She has expertise in designing and building digital ecosystems to improve care coordination and community overdose prevention efforts. In 2021, Dr. Claborn received an international award from Google for her work developing, TxCOPE, a digital platform to improve data collection and inform real-time overdose community response efforts in Texas. She has built strong multisectoral partnerships to advance community-level, coordinated overdose response efforts. Dr. Claborn’s current work seeks to use innovative methods to combine traditional and non-traditional overdose surveillance methods to inform data-driven community response.