Naoya Okamoto
Bio
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.
Links
- Personal Website
- https://www.naoyaokamoto.com/
- Twitter / X
- -
- LessWrong
- -
Grants
from Long-Term Future Fund
Discussion
Sign in to join the discussion.
No comments yet. Be the first to share your thoughts.
Details
- Last Updated
- Mar 22, 2026, 11:48 PM UTC
- Created
- Mar 20, 2026, 2:55 AM UTC