In the first year of the The Berkowitz Living Laboratory Collaboration, two outstanding scientists were selected to serve as the inaugural Berkowitz Fellows. They led collaborative research studies, published landmark research, and helped build bridges across countries and institutions:
2020-2021 Berkowitz Fellows
Noam Barda received his MD from Tel-Aviv university. Barda's medical specialty is public health and epidemiology. He received his PhD from Ben-Gurion university, where his doctoral dissertation focused on computational methods to improve cardiovascular disease prediction models. He also has a degree in computer science (BSc). Barda is head of epidemiology and research at Clalit Research Institute, the research institute for the largest health fund in Israel. There and at Harvard Medical School's DBMI, his research focuses on the intersection of epidemiology, machine learning and biostatistics, often with projects that are meant for rapid implementation in clinical settings within the health fund. More specifically, his research interests include issues around medical predictive models and causal inference from observational data.
Noa Dagan is a public health physician and researcher. She holds an MD and an MPH from the Hebrew University, and a Ph.D. in Computer Science from Ben-Gurion University. Dagan is the director of data and AI-driven medicine at the Clalit Research Institute – the research institute of Israel's largest healthcare organization, insuring and treating over 50% of the Israeli population. Her responsibilities include the development and implementation of digital healthcare solutions to promote preventive, proactive and personalized medicine. She leads the entire lifecycle of AI-driven interventions, from conception, through machine-learning modeling, to implementation in medical practice. Dagan's research focuses on practical implementations of machine-learning algorithms using clinical data, with a specific interest in the prevention of cardiovascular events and osteoporotic fractures. Dr. Dagan is also active in research of ethical aspects of machine-learning models such as fairness.