The AI for Science Summer School 2026 is a five-day program hosted at RIKEN-iTHEMS, bringing together early-career researchers interested in applying modern machine learning methods to scientific problems. The school will cover both foundational lectures and hands-on coding sessions, with topics including machine learning basics, generative models, Bayesian and simulation-based inference, foundation models and LLM agents.

Venue: RIKEN-iTHEMS

Date: 2026.08.10 -08.14

Invited Lecturers

To be confirmed

- Bayesian Inference / Simulation-Based Inference

- LLMs and Agent Systems

- Symbolic Regression

Hands-on coding session

Yangy-yang Tan, Jinyang Li, Victor Kawasaki-Bborruat

• Regression and Classification

• Dimension Reduction and Clustering

• Parameter Inference

• Generation

• TBA

Local Organizing Committee

• Catherine Beauchemin (RIKEN)

• Kenji Fukushima (UTokyo)

• Koji Hashimoto (KyotoU)

• Tetsuo Hatsuda (RIKEN)

• Satoshi Iso (RIKEN/KEK)

• Masato Taki (Rikkyo U./RIKEN)

• Akinori Tanaka (RIKEN)

• Yang-yang Tan (UTokyo)

• Lingxiao Wang (RIKEN/UTokyo)