Liat Shenhav

Liat Shenhav is an Assistant Professor at the Institute for Systems Genetics and the Department of Microbiology at New York University School of Medicine, with affiliations in the Department of Computer Science at the Courant Institute and the Center for Data Science. She leads the Shenhav Lab, which focuses on computational biology and AI-driven solutions for women’s and children’s health, particularly fertility, pregnancy, and lactation. Her work integrates systems biology, machine learning, and multi-omics data to address challenges in maternal and infant health.

• Education: PhD in Computational Biology from UCLA (2020).
• Research Interests: Microbiome dynamics, human milk composition, AI in healthcare, trajectory analysis, and biomarker discovery.

Her lab develops cutting-edge computational methods like FEAST, CTF, and DVT-Net to analyze microbiome and medical imaging data. Current projects include studying the role of breastfeeding in shaping infant microbiomes, early detection of preeclampsia via retinal imaging, and understanding reproductive tract microbiota’s impact on fertility.

Awards include the NIH New Innovator Award (DP2, 2024) for breakthrough research on breastfeeding and respiratory health. Collaborations span obstetrics, pediatrics, ophthalmology, and computational biology.

Labs/Teams: Shenhav Lab at NYU Langone, collaborations with Courant Institute, and global health partners like the CHILD Cohort Study.