I am a PhD student in the Clinical Decision Making Group (MEDG) in MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) supervised by Dr. Peter Szolovits.
My research focuses on machine learning with clinical data to predict and stratify relevant human risks, encompassing unsupervised learning, supervised learning, structured prediction. My work has been applied to estimating the physiological state of patients during critical illnesses, modeling the need for a clinical intervention, and diagnosing phonotraumatic voice disorders from wearable sensor data.
I was selected as a 2016 EECS Rising Star, was a joint Microsoft Research/Product intern at MSR-NE, and co-organized the NIPS 2016 Machine Learning for Healthcare (ML4HC) workshop. My work has appeared in KDD, AAAI, IEEE TBME, MLHC, JAMIA, and AMIA-CRI.
Prior to MIT, I received B.S. degrees in computer science and electrical engineering at New Mexico State University as a Goldwater Scholar, worked at Intel Corporation, and received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar.