I am a 4th year PhD candidate in the Stanford Machine Learning Group co-advised by Andrew Ng and Percy Liang. I am interested in developing and deploying artificial intelligence systems for medical applications, in an effort to augment clinicians and improve healthcare delivery worldwide. I have developed several high-performance ML algorithms for clinical medicine (CheXNet, CheXNeXt, MRNet, arrhythmia), curated large datasets that can facilitate advancements of ML methods (SQuAD, MURA, CheXpert), and led several interdisciplinary research teams as part of the AI for Healthcare Bootcamp at Stanford.
My research has been published in medical journals including Nature Medicine and PLOS Medicine, and CS conferences including ACL (best paper award), EMNLP (best paper award), AAAI and CHI. My work has been covered in the popular press, including Washington Post, The Economist, WIRED, and MIT Technology Review. I’m a Stanford Accel Innovation Scholar ‘18, and a Tau Beta Pi graduate ‘15. Prior to my PhD, I received my B.S. from Stanford in Computer Science with distinction and honors in 2015 and my M.S. also from Stanford in 2018.