About me. I work at the intersection of medicine and machine learning, and I’m excited about the potential of new technology to improve the quality and accessibility of healthcare. I am currently a research scientist at the National Institutes of Health in the NHLBI’s Imaging AI Program. Previously, I graduated with my Ph.D. and M.S. from Stanford University and my B.S. from Rice University. Most of my research has focused on developing and evaluating deep learning methods for medical image analysis. Please click here for more info on my research and here for my CV.
Brief graduate bio. At Stanford, I was lucky to be advised by Drs. Christopher Ré and Curtis Langlotz, affiliated with the Stanford AI Lab and the Center for Artificial Intelligence in Medicine and Imaging. I’m also grateful to have been supported by a Hertz Fellowship, an NSF Graduate Research Fellowship, and a Stanford Graduate Fellowship in Science and Engineering as the Texas Instruments Fellow. During my graduate career, I interned with the Bill and Melinda Gates Foundation and enjoyed collaboration with the NIH, specifically the NHLBI’s Imaging AI Program.
Brief undergraduate bio. I graduated summa cum laude from Rice University with a B.S. in Electrical Engineering and a minor in Global Health Technologies in 2017. At Rice, I worked with Dr. Behnaam Aazhang in the Rice Neuroengineering Initiative and with Drs. Rebecca Richards-Kortum and Maria Oden in the Rice360 Institute for Global Health Technologies. During undergrad, I spent time at the Polytechnic University of Malawi through an internship with Rice360 learning about healthcare technology and accessibility.