I am a Ph.D. student supervised by Kengo Kamatani at the Institute of Statistical Mathematics (ISM), Tokyo, Japan.
I view learning and inference as stochastic processes, and study how computational randomness is transformed into statistical performance.
I am particularly interested in Monte Carlo and stochastic optimisation algorithms. The two classes of algorithms appear to be converging towards similar dynamics as they improve: largely deterministic motion with just enough randomness.
I study how these algorithms behave especially when applied to complex and large-scale models arising from challenging inference tasks in health and well-being research.
Qualifications
Ph.D. in Statistical Science, 2028 (expected)
Graduate University for Advanced Studies, SOKENDAI, Japan
B.Sc. in Mathematics, 2023
University of Tokyo, Japan
Positions
Research Fellow, 2025.4 – present
Graduate University for Advanced Studies, SOKENDAI, Japan
Supported by JST BOOST, Japan Grant Number JPMJBS2412.
Data Scientist, 2024.9 – present
PreMedica Inc., Tokyo, Japan
Consulting on data-driven improvements to healthcare and well-being services.
Research Visits
University of Bristol, UK, 2026.9.21-10.21
Supervised by Prof. Christophe Andrieu at the School of Mathematics
Ulm University, Germany, 2025.7.13–26
Host: Prof. Evgeny Spodarev at the Institute of Stochastics
National University of Singapore, 2025.6.1–30
Host: Prof. Alexandre Thiéry at the Department of Statistics & Data Science
University College London, UK, 2024.11.4–12.2
Host: Prof. Alexandros Beskos at the Department of Statistical Science
Awards
Best Poster Award, 2025.3
19th Spring Meeting of the Japanese Statistical Society
Director’s Award, 2025.3
Japanese Statistical Society Certificate
Service
Reviewing for Bayesian Analysis, Journal of Machine Learning Research
Languages
Japanese (native), English (fluent), Mandarin Chinese (fluent), German (A2)