Research focus is the application of mathematical and economic models to evaluate disease prevention and treatment programs. Current research focuses on HIV and drug abuse interventions, hepatitis B screening and vaccination, pandemic influenza preparedness, and bioterror response planning.
Our group has two synergistic goals: To understand how brains work; this will advance treatment of neurological diseases. And to build computers that work like brains; this will increase computational power a million fold. To these two ends, we are building large-scale neural models to link cellular-level biophysical processes with the system-level functions that they enable (e.g., cognition), through an interdisciplinary effort that brings electronics and computer science in contact with neurobiology and medicine.
Michael Baiocchi, Ph.D., is an interventional-statistician, creating interventions and the means for analyzing them. He specializes in creating simple, easy to understand statistical methodologies for getting reliable results out of messy data and messy situations. His research is in nonparametric estimation and design-based inference. His main lines of applied research are in prevention of gender-based violence and health outcomes/health policy. He’s also done work in educational interventions, criminology, smoking prevention, and pediatric care.
Research Interests: Mining electronic health records using machine learning and natural language processing. Developing artificial intelligence systems for information extraction and decision support.