I am a Postdoctoral Associate at MIT in the Computer Science and Artificial Intelligence Laboratory (CSAIL) with Prof. Marzyeh Ghassemi. My interests span Time Series, Machine Learning, Data Mining, NLP, Fairness in AI Systems, and applications to understand and improve Health.
I aim to build responsible machine learning systems from partial information. The projects that excite me the most: (1) robustly model complex time-varying systems, (2) prevent perpetuating bias via machine learning, and/or (3) have impact through real-world deployment.
Some recent highlights:
TOXIGEN: constructing large, diverse hate speech datasets with large language models to train better hate speech classifiers (ACL'22)(dataset)
Learning to stop early and classify ongoing time series in time-sensitive domains (see KDD'19 and KDD'20 papers)
Methods for recovering models of annotators' partial sequential labeling behavior from machine learning datasets (see AAAI'22 and SDM'22 papers)
Explainability for time series and NLP models (see CIKM'21 and ACL'20 papers)
All papers are collaborations, please see my full list of publications.
Program Committee: AAAI, CVPR, ICCV, ACL, EMNLP, NAACL, KDD, NeurIPS Datasets & Benchmarks, COLING
Led Deep Learning with PyTorch tutorial for undergrads (2019)
WPI data science council, WPI graduate student senate, WPI Arts & Sciences council, Organized WPI deep learning reading group
Before MIT, I received my PhD in Data Science from Worcester Polytechnic Institute in 2021, where I was a GAANN Fellow advised by Professors Elke Rundensteiner and Xiangnan Kong. I also interned at Microsoft and UMass Medical School. Before graduate school, I received a B.A. in Applied Math from SUNY Geneseo in 2016.
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.