John Bollenbacher is a Research Data Scientist at RTI International and a PhD candidate at Indiana University’s Center for Complex Networks and Systems. His expertise involves applying state of the art machine learning and statistical methods to problems in public health, social media studies, and environmental science. He has extensive experience with modeling and simulation as well as model validation, including dynamical equations models and agent-based models in epidemiology, social science, physics, and complex systems science.
His most recent work leverages natural language processing (NLP), Bayesian statistics, and causal interference methods to measure the impact of social media on public health outcomes during the COVID-19 pandemic, including whether online antivaccine sentiments may be a driver of vaccine hesitancy. Bollenbacher is also currently involved in the RECOVER Initiative—created by the National Institutes of Health (NIH)—which was designed to study the long-term effects of COVID-19. In this study, he analyzed text data from Electronic Health Records to look for previously undocumented symptoms of long COVID.
