Dr. Serena Yeung-Levy is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.
Dr. Serena Sanulli's lab studies the organizing principles of the genome and how these principles regulate cell identity and developmental switches. They combine Biochemistry and Biophysical methods such as NMR and Hydrogen-Deuterium Exchange-MS with Cell Biology, and Genetics to explore genome organization across length and time scales and understand how cells leverage the diverse biophysical properties of chromatin to regulate genome function.
Home Department: Radiology
Faculty Advisor: Adam Wang
Talk Title: Fast kV switching for improved material decomposition with photon counting X-ray detectors
Event: SPIE Medical Imaging 2022
Supported by The Matthew Frank Family
Home Department: Biomedical Data Science
Faculty Advisors: Jonathan Chen and Fernando Alarid-Escudero
Talk Title: Discrete-Event Simulation Model for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline
Event: American Medical Informatics Association (AMIA) 2025 Annual Symposium
