I’m a PhD candidate in Information Science at Cornell University, where I’m advised by Matthew Wilkens. My research focuses on developing and evaluating natural language processing tools and large language models with a specific focus on clinical and biomedical purposes.

Here are a few research directions I have worked on and I continue being passionate about:

1. Advancing evaluation approaches to assess clinical technology: I developed VERT, an LLM-based metric for the assessment of radiology reports, with Jean-Philippe Corbeil and Asma Ben Abacha. I created the CQA-Eval framework for the evaluation of multi-paragraph model-generated answers to consumer health questions with Lucy Lu Wang and Yue Guo. At NYC Health + Hospitals, I demonstrated that revising alert criteria can reduce unnecessary alerts by up to 94%, while improving alert design can decrease overridden alerts by up to 64%.

2. Advancing scientific question answering systems: at the Allen Institute for Artificial Intelligence (Ai2) under the guidance of Jay DeYoung I’ve built a system that suggests reformulated queries to Asta users to assist them with refining their scientific questions and retrieving the desired information. Our system increases recall of relevant scientific documents by 50%.

3. Analyzing user needs at a large-scale: by fine-tuning DistilBERT models I analyzed user needs and support strategies in endometriosis online communities finding that patients need easier access to appointments; I then expanded this work by analyzing patients’ perceptions of ablation and excision surgery with few-shot learning. With Ian Lundberg and Matthew Wilkens I have designed a randomized survey experiment with 3,000 participants to measure the causal effect of character gender on reader preferences. I found that character gender has a minimal effect on readers’ preferences, contradicting a long standing belief in the publishing industry that men and boys are only interested in reading about people of the same gender identity.

I strive to ground my work through the theoretical frameworks of ethics of care and studying up. I enjoy using a combination of quantitative - NLP, causal inference, statistical analysis - and qualitative methods - surveys, annotations, interviews.

News

Mar 2026	I am joining Microsoft Healthcare & Life Sciences this Summer ‘26 as a PhD Research Intern working on AI for Nursing!
Jan 2026	The Cornell Chronicle covered my paper on gender and readership and I was invited to speak about it on The Last Show with David Cooper.
Dec 2025	My Research Intern position at the Allen Institute for AI is extended until April 2026
Sep 2025	My paper “Causal Effect of Character Gender on Readers’ Preferences” is accepted to CHR 2025!
Feb 2025	Paper published in the Journal of Medical Internet Research!