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SUNY Upstate Medical University

SUNY Upstate Medical University

Team Leader

Prof. Stephen Faraone (PhD)

Distinguished Professor
+ 315.464.3113
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Team Staff

Dr. Ruth Weinstock (MD, PhD)

Distinguished Service Professor
+ 315.464.9008
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Dr. Yanli Zhang-James (PhD)

Associate Research Professor
+ 315.436.5218
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Institute Presentation

SUNY Upstate Medical University in Syracuse, NY, is the only academic medical center in Central New York. Affiliated with the State University of New York, Upstate’s mission is to improve the health of the community through education, biomedical research and health care. Upstate focuses on the most prevalent human diseases, including cancer, diabetes, nervous system and psychiatric disorders, vision, heart disease, and infectious diseases.

Our Joslin Diabetes Center/Endocrinology Center at SUNY Upstate Medical University in Syracuse, NY is the only diabetes center in the region, serving >20 counties in central upstate NY. There were 35,000 outpatient visits in FY 2019-2020. The center supports a multidisciplinary team approach to effective diabetes management for pediatric and adult patients. Team members include adult and pediatric endocrinologists, a podiatrist, physician assistants, nurse practitioners, dietitians, nurse diabetes educators, a pharmacist and social workers. There are 6 fellows; Other specialists (psychologists, cardiologists, nephrologists, ophthalmologists, etc.) are also available as needed.

Our Neuropsychiatry Predictive Modelling Lab includes a team of top research professors, MD/PhD students and scientists who focus on bioinformatics and machine learning approaches to understanding the nature and causes of mental disorders including ADHD, Schizophrenia and Alzheimer’s with an ongoing research emphasis on psychiatric genetics and psychopharmacology.

Using real world data, findings, and infrastructure, the SUNY team will develop accurate statistical prediction models, based on the complex interplay of clinical and sociodemographic characteristics. Furthermore, the team will be using their expertise in bioinformatics, biostatistics, and causality analyses to aid causal modelling with real world data in order to provide new insights into disease patterns and help improve the safety and effectiveness of health interventions.