Hi! I'm an Assistant Professor of Data Science at the University of Virginia. I am spending the 2023-2024 academic year in Cambridge, MA where I am a Visiting Assistant Professor at MIT. Previously, I was a postdoc at MIT working with Marzyeh Ghassemi. Before that, I did my PhD in Data Science at WPI where I was advised by Elke Rundensteiner and Xiangnan Kong.
I am recruiting highly-motivated students to join my group at the University of Virginia. Please email me with your CV if you feel you're a good fit for my group!
I work on making machine learning responsible and trustworthy enough for deployment in shifting environments, especially those in healthcare. To achieve this, I work on building:
Robust methods for learning from data and labels that are are biased, missing, or noisy
Models that generalize and adapt to ever-shifting distributions and requirements
Tools to make models meet strong human requirements like early warnings, explainability, updatability, and safety/fairness.
Currently, I am most excited to work on:
post-training interventions for large [language] models (especially model editing)
pre-training for time series and multi-modal models
automatically detecting implicit bias in natural and AI-generated language at scale
Keywords: Updatable Machine Learning, Time Series, Large Language Models, Robustness, Interpretability, Fairness.
Outside of research, I enjoy bouldering, biking, books (science fiction/science fact), birding, juggling, vegan cooking, and guitar. I also spent a summer living at BioSphere 2 in Arizona.