B18 Robust Benchmarking for Machine Learning of Clinical Entity Extraction

I am a third year PhD student at MIT CSAIL, advised by David Sontag in the Clinical Machine Learning group. In my research, I tackle various challenges within clinical natural language processing, including: Clinical entity normalization Extraction from longitudinal clinical notes Creation of smarter electronic health records Previously, I earned a BS and MS in Computer Science at Stanford. While there, I researched in the SNAP Group under Jure Leskovec and Marinka Zitnik, where I used biological networks to predict disease-gene associations and polypharmacy side effects. I've also had internship stints at Google (2015, 2017) and Flatiron Health (2016, 2018). I am passionate about issues surrounding diversity in computer science. I recently completed my term as an officer for GW6 (Graduate Women in Course 6 at MIT), and I'm on the Dean of Engineering's graduate advisory committee for Diversity, Equity, and Inclusion.

I am a sophomore at Marquette University and am majoring in nursing. I have a strong desire to help others and hope to gain more experience in the medical field. My goal is to collaborate with other healthcare professionals and continue to expand my knowledge of the field. I was in the Launch Medicine and Healthcare strand at my high school, where I learned more about different careers in health care and expanded my knowledge through work outside the classroom setting. I got to collaborate in groups and work with a variety of health care professionals and conduct various projects throughout the year.

I am participating in SuperUROP to experience advanced research and use the academic skills I've gained in undergraduate classes, while producing concrete impact in a problem space that I'm passionate about. I have previous UROP experience in the Media Lab and have taken graduate level machine learning (ML) and human-computer interaction (HCI) courses. I hope to further my understanding of ML, HCI, and health care while enabling NLP research on clinical text

David Sontag joined the MIT faculty in 2017 as Hermann L. F. von Helmholtz Career Development Professor in the Institute for Medical Engineering and Science (IMES) and as Associate Professor in the Department of Electrical Engineering and Computer Science (EECS). He is also a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Professor Sontag’s research interests are in machine learning and artificial intelligence. As part of IMES, he leads a research group that aims to transform healthcare through the use of machine learning. Prior to joining MIT, Dr. Sontag was an Assistant Professor in Computer Science and Data Science at New York University’s Courant Institute of Mathematical Sciences from 2011 to 2016, and postdoctoral researcher at Microsoft Research New England from 2010 to 2011. Dr. Sontag received the Sprowls award for outstanding doctoral thesis in Computer Science at MIT in 2010, best paper awards at the conferences Empirical Methods in Natural Language Processing (EMNLP), Uncertainty in Artificial Intelligence (UAI), and Neural Information Processing Systems (NIPS), faculty awards from Google, Facebook, and Adobe, and a NSF CAREER Award. Dr. Sontag received a B.A. from the University of California, Berkeley.