Hello! I’m Hiro.
Hirofumi Shiba is a Ph.D. student jointly supervised by Kengo Kamatani and Keisuke Yano at the Institute of Statistical Mathematics (ISM), Tokyo, Japan.
My research focuses around Monte Carlo algorithms and numerical computation. By making them more efficient, scalable, and automated, I aim to broaden the applications of statistics and machine learning.
Before pursuing my Ph.D., I studied Mathematics at the University of Tokyo.
Interests
- Monte Carlo Computation
simulation techniques such as MCMC, SMC & PDMP - Bayesian Statistical Modelling
especially applications to Political Science & Biostatistics - Bayesian Machine Learning
such as Nonparametrics & Kernel Methods
Research
My research interests revolve around developing and analyzing stochastic simulation algorithms, by leveraging insights from their continuous-time limit dynamics. From this perspective, algorithms reveal their intrinsic properties, and my work aims to unify the understanding of various sampling algorithms under a common mathematical framework, i.e., gradient flows on the space of probability measures \(\mathcal{P}(X)\).
On the other hand, I contribute to the R package YUIMA, and maintain the Julia package PDMPFlux.jl. Additionally, I engage in Bayesian data analysis in collaboration with healthcare and engineering companies.
Education
Ph.D. in Statistical Science, 2028 (expected)
Graduate University for Advanced Studies, SOKENDAI, Japan
B.Sc. in Mathematics, 2023
University of Tokyo, Japan
Experience
Cooperative Researcher, 2023.4 – present
RCAST, the University of Tokyo
Data Scientist, 2023.4 – present
PreMedica Inc., Tokyo, Japan