I am a Ph.D. student at Shalit Lab, Technion - Israel Institute of Technology.
I am a researcher and developer with specific interest in machine\deep learning and causal inference for healthcare applications, experienced with different data modalities such as longitudinal signals, tabular data, and imaging.
My current research is about finding and understanding relations between brain signals as measured by EEG and other physiological signals to improve patient’s care in intensive care unit.
Previously, as a researcher at Segal Lab - Weizmann Institute of Science (2020-2021), throughout the COVID-19 pandemic, most of my effort was to develop strategic tools for public-health officials and policymakers. We devised national symptoms surveys for identifying virus spread clusters, developed machine-learning models for predicting the future number of hospitalized patients and deaths, analysed what-if scenarios that project the consequences of various national strategies, and provided real-time assessment of vaccine effectiveness at the national level.
As an algorithms team member (2018-2019) at Zebra Medical Vision, I developed deep-learning algorithms for automatic analysis of medical imaging (mainly CT and X-rays), which are currently being used by healthcare providers to improve population health.