William Brannon
I’m a PhD student at MIT’s Center for Constructive Communication and Media Lab, advised by Deb Roy. During the PhD, I’ve interned with Brian Thompson at Amazon AI. I’m also one of the leads on the Data Provenance Initiative, an ongoing effort to audit and analyze model training datasets. Previously, I earned an MS at the Media Lab and a bachelor’s degree in mathematics from the College of William and Mary. Between undergrad and graduate school, I worked as a data scientist for various political groups and campaigns, on topics including predictive models of donor and voter behavior, design and implementation of field experiments, and data infra engineering.
I’m interested in several topics related to socially aware AI and applications to computational social science. Currently, I’m interested in and working on:
- Data-centric AI: large language models, the role of training data, and evaluation.
- AI for computational social science: use of machine learning and LLMs to model and understand persuasion, opinion change and media ecosystems.
- Socially aware AI: graph deep learning and models for social network settings, especially for text-attributed graphs (TAGs).
If you’re interested in these areas and want to chat or collaborate, get in touch! The best way to reach me is by email: will.brannon@gmail.com or wbrannon@mit.edu.
Fore more info, you can also download my CV or check out my publications.
news
Sep 20, 2024 | Our new paper “On the Relationship between Truth and Political Bias in Language Models” has been accepted for a main-conference presentation at EMNLP 2024! |
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Aug 15, 2024 | I presented our work “ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddings” at TextGraphs 2024, hosted this year at ACL in Bangkok. |
Jul 18, 2024 | Our paper “The speed of news in Twitter (X) versus radio” was presented at this year’s IC2S2! Check out a recorded version of the talk here. |
Jul 10, 2024 | Our paper “A Large-Scale Audit of Dataset Licensing and Attribution in AI” has been accepted at Nature Machine Intelligence! This paper represents the first phase of work on the Data Provenance Initiative. |
Jul 02, 2024 | CSCW 2024 has accepted our paper “Bridging Dictionary: AI-Generated Dictionary of Partisan Language Use.” |