The placenta is an important organ that allows the exchange of gases and nutrients between a mother and baby. When the placenta does not form or function correctly, it can lead to serious pregnancy complications and health risks for both mother and baby. Yet, despite its importance, studying the placenta during pregnancy remains difficult due to ethical and safety reasons. Studies in animal models provide limited information as the placenta can vary significantly between species. This CAREER project will use computer simulations and machine learning to understand how blood flow controls placental development. The project will study how changes in placental structure affect oxygen delivery to the baby. The project’s outcome will improve understanding of placental function and guide future strategies to improve maternal and fetal health. The project also includes an integrated education and outreach plan. Through a “Learning by Teaching” approach, engineering students will strengthen their technical knowledge and apply core engineering principles to explain the mechanics of pregnancy. Students will also build science communication skills and engage broader audiences in understanding maternal and fetal health through an engineering lens. This project will establishe a novel engineering framework for studying the placenta that integrates experimental data with physics-based modeling and machine learning within a unified multiscale platform. The goal is to advance fundamental understanding of placental development and function in both healthy and pathological states through three complementary computational models that target key aspects of placental physiology. These include (1) characterization and quantification of intervillous space (IVS) hemodynamics, (2) determination of how mechanical cues regulate placental villi development through trophoblast mechanotransduction, and (3) quantification of how placental maldevelopment compromises oxygen delivery to the fetus. A c