Summary
Samantha Piekos is an interdisciplinary computational biologist and Assistant Professor with nine years of experience applying AI and systems biology to precision medicine, particularly maternal-fetal health. Trained as both a bench scientist (PhD Stanford, stem cell biology) and data scientist, she builds and analyzes multi-omics, wearable, clinical, and environmental datasets to map molecular networks and predict obstetric risks. Her work at institutions including Google, Institute for Systems Biology, and University of Pennsylvania combines ML, LLMs, and knowledge graphs to detect early deviations in biological transitions and design targeted interventions. She also translates complex science to broad audiences as founder and president of a Stanford science writing outreach group and organizer of student science communication programs. Based in Philadelphia, she studies climate-mediated exposures (e.g., wildfire smoke, extreme heat) on pregnancy outcomes, blending population-level epidemiology with personalized, longitudinal deep-phenotyping. Colleagues value her collaborative, team-oriented approach and rare dual fluency in wet-lab epigenomics and computational AI methods.
8 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.), Biological Sciences; Psychology, 3.92, Bachelor of Science (B.S.), Biological Sciences; Psychology, 3.92 at University of Notre Dame
Doctor of Philosophy (Ph.D.), Stem Cell Biology and Regenerative Medicine, 4.0, Doctor of Philosophy (Ph.D.), Stem Cell Biology and Regenerative Medicine, 4.0 at Stanford University
English, Spanish