Jenny Y. Huang

Welcome everyone!

I am a first year PhD student studying machine learning at MIT, grateful to be working in the department of Electrical Engineering and Computer Science in LIDS with Professor Tamara Broderick!

Before coming to MIT, I did my undergrad at Duke University, where I worked with a host of amazing people, including Jason Xu, David Dunson, Cynthia Rudin, and Rick Durrett. Before Duke, I went to the NC School of Science and Math, where I developed a love for all things STEM!

Outside of STEM, I enjoy poetry (particularly, nature-themed) and dance (hip-hop, swing, ballet)!

Interests

Bayesian Inference
Robust ML
Epidemic Modeling
Causal Inference

Education

PhD in Electrical Engineering and Computer Science (in progress)
Massachusetts Institute of Technology
BSc in Statistical Science, 2023
Duke University
BSc in Computer Science, 2023
Duke University

Publications

Jenny Y. Huang, Raphaël Morsomme, David Dunson, Jason Xu (2022). Detecting Changes in the Transmission Rate of a Stochastic Epidemic Model.

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(2022). Ecological Drivers of Parasite Species Richness: a Novel Approach to Addressing Sampling Bias. Ecography.

Gaurav Parikh*, Jenny Huang*, Albert Sun*, Lesia Semenova, and Cynthia Rudin (2022). Moving towards a more equal world, one ride at a time: Studying Public Transportation Initiatives using interpretable causal inference. NeurIPS-22.

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Laura Boyle, Sofia Hletko, Jenny Huang, June Lee, Gaurav Pallod, Hwai-Ray Tung, and Richard Durrett (2022). Selective sweeps in SARS-CoV-2 variant competition. Proceedings of the National Academy of Sciences.

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Achal Aswathi, Volodymyr Minin, Jenny Huang, Daniel Chow, and Jason Xu (2022). Fitting a stochastic model of intensive care occupancy to noisy hospitalization time series during the COVID-19 pandemic. StatMed.