Research overview

My research is in Natural Language Processing and Machine Learning, with an emphasis on applications in health.

Working in the domain of health naturally motivates the methodological problems that I have worked on. For example, these include: model interpretability; learning with limited supervision from diverse sources; human-in-the-loop/hybrid systems; and trustworthiness of model outputs. For more details, see recent publications here.

On the applications side, one thread of my research concerns developing language technologies to automate (or semi-automate) biomedical evidence synthesis. Here is an episode of the NLP highlights podcast in which I discuss this work, here is a (brief) talk I gave at SciNLP 2020, and here is an article written for a lay audience about the effort. Elsewhere, I have worked on models for processing notes in Electronic Health Records.

A random sample of recentish publications

David Lowell, Brian Howard, Zachary C. Lipton. Byron C. Wallace. Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data EMNLP; 2021.

Pouya Pezeshkpour, Sarthak Jain, Byron C. Wallace and Sameer Singh. An Empirical Comparison of Instance Attribution Methods for NLP NAACL; 2021.

Eric Lee, Byron C. Wallace, Karla Galaviz, and Joyce C. Ho. MMiDaS-AE: Multi-modal Missing Data aware Stacked Autoencoder for Biomedical Abstract Screening ACM Conference on Health, Inference, and Learning (CHIL); 2020.


06/27/2022 NSF Medium

The NSF has awarded me and Zack Lipton a grant to work on summarization methods for consequential domains (like healthcare).

05/13/2022 ACL Outstanding Paper Award

Our paper, “Evaluating Factuality in Text Simplification", was selected as an Outstanding Paper at ACL 2022

03/18/2021 Student Paper Award @ AMIA Summits

Our paper — led by my PhD student Ben Nye — received the best student-led paper award at the AMIA (Virtual) Summits

01/20/2021 Lutron Award

I received the 2021 Joel and Ruth Spira Excellence in Teaching Award for the Khoury College of Computer Sciences


My work has been supported with grants from the National Institutes of Health, National Science Foundation (including a CAREER grant), the Army Research Office, Seton hospital, Amazon and seed funds from Brown University.