Naoya Okamoto

Naoya Okamoto is an early-career researcher exploring AI safety and alignment, based in the United States. They graduated from Fordham University in 2023 and have a background in proof-based mathematics. Inspired by Brian Christian's book The Alignment Problem, Okamoto pursued upskilling in machine learning through the University of Illinois Urbana-Champaign's Mathematics of Machine Learning course in summer 2023, funded by a Long-Term Future Fund grant. After exploring theoretical alignment research, they shifted focus toward empirical alignment research, working through the MLAB curriculum in 2024. They have also interned at the U.S.-Japan Council and volunteered with the Human Restoration Project, a progressive education nonprofit. Outside of AI safety, they are interested in AI policy advocacy and biosecurity.

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https://www.naoyaokamoto.com/

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