About me

Currently working in a stealth startup. Previously Ph.D student in Computer Science at the Weizmann Institute of Science, Segal lab.

My research interests surround applying data science and machine learning methods to real-world medical problems by working with rich and diverse medical datasets, and conducting joint work with domain experts - physicians and policy makers.

For example, 20-year nationwide electronic health-records are used for research spanning topics such as: prediction of childhood obesity and gestational diabetes at an early stage, understanding the effects of cesarean section birth on long term pediatric health, and studying the comparative effectiveness of drugs given to cardiovascular disease patients. Another research direction focuses on prospective datasets collected at the Segal lab. These include a long-term study on health and lifestyles of over 10,000 healthy Israeli subjects.

During 2020-2021, most of my effort has been directed towards collection and analysis of critical data related to the ongoing COVID-19 pandemic: Daily symptom surveys, construction of hospitalization and mortality models and real-time assessment of vaccine effectiveness at the national level.

Also see OSS: PyMSM: Python package for Competing Risks and Multi-State models for Survival Data