Hi! I'm a postdoc at the Massachusetts Institute of Technology working with Prof. Marzyeh Ghassemi. My research spans machine learning, data mining, and applications to improve healthcare.
I received my PhD in Data Science from WPI in 2021, where I was a GAANN Fellow advised by Professors Elke Rundensteiner and Xiangnan Kong.
I am on the academic job market for tenure-track positions in CS/ECE/Data Science
I'm making machine learning and data mining methods deployable in complex, time-varying environments. I focus on core problems in time series and natural language data that arise in healthcare, where:
Data and labels are missing and noisy
Models must adapt to quickly shifting distributions and requirements
We have strong human-facing requirements like early predictions, interpretability, and safety/fairness.
The projects that excite me the most: (1) robustly model dynamic environments through time series, (2) prevent perpetuating bias via machine learning and/or (3) have impact through real-world deployment.
GRACE: Continually editing pre-trained models thousands of times in a row during deployment (preprint)
ToxiGen: Constructing large, diverse hate speech datasets with large language models to train better hate speech classifiers (ACL'22 + dataset)
Timely and Actionable Time Series Models (see KDD'19; KDD'20; CIKM'22)
Robustness to uncertain/incomplete labels (see AAAI'23; AAAI'22; SDM'22; CIKM'22; AAAI'21)
Explainability for time series and NLP models ( see ACL'20; CIKM'21; ICDM'22)
Led tutorial on Deep Learning with PyTorch for undergrads
Program Committee: AAAI, WSDM, CVPR, ICCV, ACL, EMNLP, NAACL, KDD, NeurIPS Datasets & Benchmarks Track
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 rural Arizona.