We are a computational biology research group dedicated to developing algorithms that enhance the health of women and children, focusing on fertility, pregnancy, and lactation.
We're not just scientists; we're pathfinders seeking to bring algorithmic precision to areas of health where it's been previously absent.
Welcome to the Shenhav Lab. I’m Liat Shenhav, an Assistant Professor at the Institute for Systems Genetics and the Department of Microbiology at the Grossman School of Medicine, with affiliations in the Department of Computer Science at the Courant Institute for Mathematical Sciences and the Center for Data Science.
We are a computational biology research group dedicated to developing mathematical models and AI algorithms to improve the health of women and children, with a focus on fertility, pregnancy, and lactation. Our aim is to enhance maternal and child health outcomes through rigorous, data-driven insights.
Through extensive data collection, bespoke algorithm development, and collaborations with experts in obstetrics, pediatrics, ophthalmology, microbiome science, and human milk research, we aim to uncover key mechanisms and identify biomarkers that drive complex biological systems.
Liat Shenhav - Lab PI
Our work sits at the confluence of data science and clinical expertise, embodying a dynamic and complex data landscape that demands the keen intellect of data scientists. These experts collaborate closely with a diverse team of clinicians, including obstetricians, ophthalmologists, pediatricians, alongside human milk scientists, nutritionists, and experimental biologists.
Interdisciplinary Teams
Advanced Algorithm Development
Pioneering Health Insights
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