About me
I am a first-year Ph.D. student in Computer Science and Engineering at the University of Washington, advised by Yulia Tsvetkov. I do research in Natural Language Processing, and I'm particularly intereted in using computational methods to model and potentially discover cognitive processes.
Before grad school, I received my B.S. and M.S.E. at Johns Hopkins with majors in Computer Science, Cognitive Science (linguistics focus), and Applied Mathematics (statistics focus). I worked as a research assistant at the Center for Language and Speech Processing advised by Philipp Koehn and Kenton Murray.
My research interests: Natural Language Processing, Multilingual NLP, Computational Sociolinguistics, Low-Resource Machine Translation, Human-Centered NLP
Please contact me at stelli [at] cs.washington.edu if you are interested in my work!
Click here to view my CV (updated Sep. 23)
Current Projects
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Medical Decision Making
I'm thinking about how to identify missing information during medical decision making and proactively seek information using large language models. Also interested in modeling "intuition" in expert domains.
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Surfacing Community Norms
How do people in different communities interact differently? What are the unspoken rules that influence and govern such interactions? This project attempts to surface linguistic and social norms in online communities.
News
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12/06/2023
I will be atteneding EMNLP 2023 in person. Looking forward to meeting everyone in Singapore!
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04/15/2023
I will be starting my Ph.D. at the University of Washington, excited to be part of Tsvetshop!
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12/20/2022
Check out our new paper "A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors."
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11/14/2022
Check out our new paper "Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns."
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10/21/2022
Check out our new paper "A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters."
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10/07/2022
Check out our new paper "PQLM - Multilingual Decentralized Portable Quantum Language Model for Privacy Protection."
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09/26/2022
Check out our new paper "End-to-End Lyrics Recognition with Self-supervised Learning."
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07/09/2022
Check out our workshop paper "Genetic improvement in the shackleton framework for optimizing LLVM pass sequences" accepted to GECCO'22. Best Presentation Award
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03/24/2022
Check out our paper "Optimizing LLVM Pass Sequences with Shackleton: A Linear Genetic Programming Framework" accepted to GECCO'22.