I am a researcher at the Machine Learning for Healthcare and Life Sciences group at the Haifa research labs in Israel, where I am developing tools to allow clients to make data-driven decisions about healthcare management and patient treatment. My current main focus is the development of tools for causal inference analysis in healthcare that can estimate the effect of treatment both on an individual and on a population.
I am a multidisciplinary researcher working in the fields of bioinformatics and computational biology, with a proven track record of leading and assisting scientific projects. My academic experience includes physics, computer science, biology, and medicine. I accumulated extensive experience in developing dynamic models, algorithms, machine learning methods, and simulation tools, as well as in analyzing high-throughput sequencing data. I have more than 10 years of experience of working in close partnership with colleagues on the design of both hypothesis generating and validation experiments, as well as working in local and international collaborations.
I completed my postdoctoral research at Columbia university, where I developed algorithms for the analysis of gene regulatory networks and the connection between changes in the network and changes in phenotype. In this context I created an algorithm to understand the mode of action through which perturbations affect cells, and created machine learning models to identify the features that contribute to disease progression and mortality.
In two previous postdoctoral positions, one at the Hadassah medical school in jerusalem, and the other at Mount Sinai school of medicine, I analyzed the dynamics of small gene-regulatory modules, focusing on accurate and efficient simulations that take into consideration the stochastic effects arising from low copy numbers.