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
Masato Taki
Rikkyo U. / RIKEN
Topic: Basics of Machine Learning
Lingxiao Wang
RIKEN / UTokyo
Topic: Generative Models
David Shih
Rutgers University
Topic: Vibe Coding and Foundation Models
TBA
To be confirmed
- Bayesian Inference / Simulation-Based Inference
- LLMs and Agent Systems
- Symbolic Regression
Yangy-yang Tan, Jinyang Li, Victor Kawasaki-Bborruat
Regression and Classification
Dimension Reduction and Clustering
Parameter Inference
Generation
TBA
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)
Contact Person: Lingxiao Wang
Office: Main Research Building 351_1
E-mail: lingxiao.wang[change it to at]riken.jp
Address: RIKEN-iTHEMS, 2-1 Hirosawa, Wako, Saitama 351-0198 Japan