Naoki Yoshida
Naoki Yoshida earned a doctorate in February 2002 for research on numerical simulations of cosmic structure formation. His career includes Harvard-Smithsonian research, a Nagoya appointment, and professorships at Tokyo and Kavli IPMU. His RIKEN team develops learning methods for noisy telescope and physics data and emulators that replace costly simulations. In 2023 he co-authored Machine Learning for Observational Cosmology with Kana Moriwaki and Takahiro Nishimichi. The review examines learning applications and computing requirements for large sky surveys.
- Now at
- RIKEN and University of Tokyo
- Works
- 416
- Citations
- 23,971
- h-index
- 62
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2002
Simulating cosmic structure
Yoshida earned a doctorate in February 2002. The thesis examined numerical simulations of the formation of large-scale structure in the universe. He also trained in aerospace engineering at Tokyo earlier in his career.
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2004–2014
Nagoya and Tokyo research posts
He was an assistant professor at Nagoya from 2004 to 2008, followed by an associate post at Kavli IPMU in Tokyo. He became a physics professor at Tokyo in 2012 and a professor at Kavli IPMU in 2014.
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2023
Machine learning for sky surveys
Yoshida, Kana Moriwaki, and Takahiro Nishimichi co-authored a 2023 review of machine learning for observational cosmology. It discusses analysis of large astronomical datasets and the computing requirements for forthcoming sky surveys. The paper reviews methods and challenges.
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As of October 2026
Learning and simulation emulators
Yoshida’s team uses learning and generative models to extract signals from noisy telescope and physics data. The team also develops emulators that replace costly nonlinear simulations for statistical analysis.
Sources and credits
Photo: www.riken.jp; Naoki Yoshida 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.