معرفی
Jonathan Bates is a Lecturer at the Yale School of Public Health, affiliated with the Yale Center for Medical Informatics. His work focuses on applying machine learning and data science to public health challenges, particularly in HIV care, falls prevention, and medical device safety.
His educational background includes:
- PhD in Biomathematics from Florida State University (2013)
- Postdoctoral Fellowship in Medical Informatics at VA Connecticut/Yale (2015)
Dr. Bates' research spans machine learning and health informatics, with expertise in natural language processing, predictive modeling, and causal inference. His work targets vulnerable populations including older adults with HIV and veterans, addressing critical gaps in fall prevention, fracture risk assessment, and healthcare delivery optimization through advanced analytics.
Analysis of his 15 most recent publications (2015-2023) reveals three dominant research thrusts: predictive modeling for geriatric falls and fractures in HIV populations, machine learning applications in medical device surveillance, and social network analysis for care coordination. These studies consistently leverage electronic health records and focus on high-impact public health problems affecting marginalized groups.
Dr. Bates maintains active collaborations across Yale University, the Veterans Health Administration, and clinical departments including Cardiology and Emergency Medicine, demonstrating strong interdisciplinary integration of methodological innovation with real-world health challenges.
