Shohei Shimizu
Shohei Shimizu works on causal discovery: methods for estimating causal relationships when randomized intervention experiments are unavailable. Shimizu, Patrik Hoyer, Aapo Hyvärinen and Antti Kerminen coauthored the JMLR paper introducing a linear non-Gaussian acyclic model for causal discovery. Shimizu wrote Statistical Causal Discovery: LiNGAM Approach. He published the book in 2022, alongside work on causal models and observational-data methods.
Timeline
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2006
LiNGAM research
Shimizu, Patrik Hoyer, Aapo Hyvärinen and Antti Kerminen coauthored the JMLR paper introducing a linear non-Gaussian acyclic model for causal discovery.
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2022
A book on causal discovery
Shimizu wrote Statistical Causal Discovery: LiNGAM Approach. He published the book in 2022, alongside work on causal models and observational-data methods.
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2023
Causal discovery software
Shimizu was among the authors of a JMLR paper describing a Python package for causal discovery based on LiNGAM. The software connects methodological research to tools researchers can use.
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As of October 2026
Research across disciplines
Shimizu collaborates across science, medicine, engineering and policy. He works in the Osaka causal-discovery lab and directs RIKEN’s causal-inference team.
Sources and credits
Photo: www.riken.jp; Shohei Shimizu profile photograph; creator not stated. License: Not stated by source. Source: riken.jp. Cropped to a square and resized. Ask us to remove or replace this photo.