My research focuses on natural language processing and data science techniques to extract useful information from scientific documents. Specifically, I investigate NLP systems for understanding biomedical text, as well as how data science and text analysis techniques can be used to identify trends in research communication. I work as a Postdoctoral Investigator at the Allen Institute for AI (AI2) in the Semantic Scholar research group. I completed my PhD in the Department of Biomedical Informatics and Medical Education (BIME) at the University of Washington in Seattle, WA, and also hold degrees in Biomedical Engineering and Physics from Johns Hopkins and MIT respectively. I am currently on the faculty job market!

I live on (in?) Capitol Hill in Seattle, WA. In my spare time, I enjoy cycling and hiking, foraging for mushrooms, playing go (weiqi), cooking, and working on miscellaneous projects. See photos from my latest exploits.


Nov 16, 2021: New preprint out: "Literature-Agumented Clinical Outcome Prediction". Led by intern Aakanksha Naik.

Oct 22, 2021: Paper to HTML Converter won the Best Artifact Award at this year's ASSETS conference!! Our demo paper can be found here.

Sep 14, 2021: We launched a public beta of Paper to HTML, which rerenders scientific papers as HTML on-demand.

Sep 7, 2021: I gave a talk at the Conference on AI and Theorem Proving (AITP) on "Mathematics in the Scholarly Literature," discussing some of our work on the S2ORC dataset.

Aug 26, 2021: Our paper on medical multi-document summarization and literature review automation has been accepted to EMNLP 2021! Led by intern Jay DeYoung.

Aug 13, 2021: My team won the AI2 Hackathon Common Good award with our project "A11y2: making research accessible, AI2 and beyond"! We developed a way to create accessible HTML renders of paper PDFs on request, which we're hoping to launch publicly soon. Awesome collab with teammates Alex Buraczynski, Daniel King, Matt Latzke, and Sam Skjonsberg.

Jul 29, 2021: I gave a talk at the Science of Science Summer School (S4) on NLP and scientific text mining.

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