Casey Meehan
Research Engineer at OpenAI
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolCasey Meehan is a research engineer at OpenAI with eight years of experience at the intersection of machine learning, privacy, and systems. His PhD work at UCSD and internships at Meta, Tesla, and Tumult Labs center on quantifying model memorization and designing provable, application-specific privacy mechanisms for settings from LLM embeddings to location and social graph data. He has demonstrated practical attacks—such as diffusion-based reconstruction of training images for self-supervised vision models—and proposed mitigation and privacy accounting techniques that inform real-world deployment. Comfortable moving between theory and engineering, he has shipped algorithms, testbenches, and production-oriented designs from analog ADC blocks to ML privacy tools. Based in San Francisco, he blends rigorous academic publication with hands-on implementation at startups and major labs, often surfacing subtle privacy risks that are overlooked in standard evaluations.
8 years of coding experience
3 years of employment as a software developer
University of California, San DiegoB.S., Electrical Engineering & Signal Processing, B.S., Electrical Engineering & Signal Processing at Brown UniversityM.S., Computational Science and Engineering, M.S., Computational Science and Engineering at Harvard University
Github Skills (1)
acl1
Programming languages (1)
Github contributions (5)
casey-meehan/location_trace_privacy
Aug 2020 - Oct 2020
Contributions:17 commits in 2 months
casey-meehan/casey-meehan.github.io
Jun 2021 - May 2023
Contributions:22 pushes, 1 branch in 1 year 11 months
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