Resume
Academic Achievements
- Publications: 'From Acceleration to Saturation: Scaling Behavior of Bootstrapped Language Model Pretraining' (October 2025); 'Optimal Variance and Covariance Estimation under Differential Privacy in the Add-Remove Model and Beyond' (September 2025); Paper accepted to ICML 2025. Awards: Recipient of DBSJ Kambayashi Young Researcher Award; Marie Skłodowska-Curie ESR Fellowship; JSPS (Japan Society for the Promotion of Science) Research Fellowship for Young Scientists; MEXT Scholarship.
Research Experience
- Worked as a Marie Skłodowska-Curie ESR at the Technical University of Munich and as a researcher at NEC Corporation.
Education
- Ph.D. in Physics from the University of Tokyo in 2017; M.S. in Physics from the University of Tokyo in 2014; B.S. in Physics from the University of Tokyo in 2012.
Background
- A research scientist at SB Intuitions/LY/LINE Corporation working on machine learning. Previously a particle physicist. Current interests include training large language models, security and privacy issues of machine learning, statistics, theoretical computer science, and physics and mathematics in general.
Miscellany
- Based in Tokyo, Japan. Social media: LinkedIn, Twitter, Github, Google Scholar.