Hirofumi Ota

Hirofumi Ota is a Project Assistant Professor at the Department of Basic Science within the Graduate School of Arts and Science at the University of Tokyo, affiliated with the Imaizumi-lab. He concurrently serves as a Visiting Scientist at the RIKEN Center for Advanced Intelligence Project in the High-Dimensional Causal Analysis Team, bridging theoretical statistics and data science applications.

His academic credentials include:

• Bachelor of Arts in Economics from Kyoto University
• Master of Arts in Economics (Statistics) from the University of Tokyo
• Doctor of Philosophy in Statistics from Rutgers University, supervised by Professor Min-ge Xie

Ota specializes in performance-guaranteed statistical inference for non-classical data science scenarios where central limit theorems fail, with core expertise in selective inference and irregular inference for discrete/non-numerical parameters. His work advances modern uncertainty quantification through conformal inference, repro samples method, and universal inference, while pioneering E-values/E-processes for sequential decision making and information aggregation in machine learning. Robust statistics applications feature prominently in his outlier detection and high-dimensional regression research, alongside econometrics contributions to quantile models and non-standard asymptotics.

Honors include:

• Best presentation award at the Conference of Japan Statistical Society (2025)
• Truman-Koehler Scholarship/Excellence Award (Rutgers University, USA)
• Grant-in-Aid for JSPS Fellows (DC1, Japan)

His professional experience encompasses statistical consulting for companies, researchers, and students at Rutgers' Office of Statistical Consulting during doctoral studies. Current research is supported by JSPS fellowship funding, though no specific grants are detailed. Ota actively contributes to academic service as a reviewer for Electronic Journal of Statistics, Journal of Computational and Graphical Statistics, Journal of Time Series Analysis, Annals of Institute of Statistical Mathematics, Econometric Reviews, and Scandinavian Journal of Statistics.

He operates within the Imaizumi-lab at the University of Tokyo, focusing on foundational statistical science, and collaborates with RIKEN's High-Dimensional Causal Analysis Team on cutting-edge causal inference methodologies for complex datasets.