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Liat Shenhav is an Assistant Professor at the NYU Grossman School of Medicine, specializing in computational biology. Her research group focuses on developing mathematical models and artificial intelligence (AI) algorithms to enhance the health of women and children, particularly in areas related to fertility, pregnancy, and lactation. With the goal of improving maternal and child health outcomes, she employs rigorous, data-driven insights. Her bespoke computational methods combine tensor factorization, time-series analysis, and machine learning along with principles of community ecology and complexity theory to uncover hidden dynamics that distinguish normal from pathological conditions. Her work on algorithms seeks to reveal interpretable relationships among multiple omic layers impacting health-related phenotypes of women and children. Key areas of her research include the human microbiome, human milk, and the dynamics of pregnancy.
Open Program in Biomedical Sciences (Vilcek Institute) covers departments like Biochemistry, Pathology, Neuroscience, Microbiology, etc.