Tobin South
Member Of Technical Staff at Stanford University
San Francisco, California, United States
Summary
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Senior🎓
Top SchoolTobin South is an AI security and agents engineer with eight years of experience building infrastructure that makes intelligent systems auditable, safe, and enterprise-ready. Currently a Member of Technical Staff at Anthropic and a Research Fellow at Stanford leading consumer-protection work for the Loyal Agents initiative, he blends hands-on engineering with policy-aware research. He completed an early, funded PhD at MIT Media Lab focused on AI security and society and has led projects at WorkOS, Microsoft Research, and government pandemic modeling that required rigorous probabilistic and systems thinking. Tobin’s background spans startup founding, VC diligence, and academic awards, reflecting a rare mix of product delivery, research leadership, and strategic evaluation. He often focuses on secure agent identity, access controls, and verifiable model attestations—areas where infrastructure and governance meet—and prefers building practical tools that can be adopted by both industry and regulators.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD AI Security - MIT Media Lab, Doctor of Philosophy - PhD AI Security - MIT Media Lab at Massachusetts Institute of TechnologyMaster of Philosophy, Master of Philosophy at University of Adelaide
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (43)
cryptography9
entropy9
forecast8
screen-scraping8
react8
ai8
tailwindcss8
twitter8
meteorology7
css7
scraper7
natural-language-processing7
tailwind7
nextjs7
google-search6
Programming languages (7)
Github contributions (5)
tobinsouth/covid19-forecasting-aus
May 2021 - Aug 2021
Code used to forecast COVID-19 cases for the Australian Federal Government from the University of Adelaide.
Contributions:234 commits, 109 pushes, 13 branches in 2 months
meteorologycasespythondata-sciencefederal-government
tobinsouth/ProcessEntropy
Sep 2019 - Sep 2021
A toolkit for calculating process entropy quickly. With specific applications to tweets.
Contributions:1 release, 46 commits, 2 PRs in 2 years
entropypythontwittertweetsentropy-rate
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