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RIKEN Mathematics & AI Symposium 2026

Mathematics and AI: Tokyo Symposium on the Mathematical Sciences and Formal Reasoning

This international symposium brings together leading researchers in the mathematical sciences, formal reasoning, and AI-driven discovery to explore the evolving relationship between mathematics and AI. The meeting will examine how AI is reshaping mathematical research, from conjecture and proof to formalization and discovery, while mathematics continues to provide fundamental ideas for the theory and reliability of modern AI. Held in Tokyo, the symposium aims to foster international dialogue and new collaborations at the interface of mathematics and AI.

Tutorial Lectures: Tuesday, August 18
Time Speaker Affiliation Title
13:00-14:00 Johan Commelin Johan Commelin Mathlib Initiative / Utrecht University A pragmatic introduction to Lean and Mathlib I
14:10-15:10 Johan Commelini Johan Commelin Mathlib Initiative / Utrecht University A pragmatic introduction to Lean and Mathlib II
15:10-15:30 Break
15:30-16:30 Sergei Gukov Sergei Gukov California Institute of Technology / Merkin Center for Pure and Applied Mathematics AI for mathematics and long-horizon & sparse-reward tasks I
16:40-17:40 Sergei Gukov Sergei Gukov California Institute of Technology / Merkin Center for Pure and Applied Mathematics AI for mathematics and long-horizon & sparse-reward tasks II
Symposium Day 1: Wednesday, August 19
Time Speaker Affiliation Title
9:30-9:45 Makoto Gonokami President, RIKEN Opening remarks
9:45-10:10 Hal Finkel Advanced Scientific Computing Research (ASCR), DOE TBA 
10:10-10:30 Break
10:30-11:30 Ravi Vakil Ravi Vakil Stanford University How AI might accelerate mathematics discovery: a realist's guide
11:30-12:10 Shin-ichi Ohta Taiji Suzuki The University of Tokyo / RIKEN AIP Theory and methodology of diffusion models with science applications: Continuous and Discrete variables
12:10-13:30 Poster Session  + Lunch
13:30-14:30 Michael Douglas Michael Douglas Harvard University CMSA / Simons Collaboration on Physics of Learning and Neural Computation / AletheAI, Inc. AI-assisted math and theoretical physics
14:30-15:10 Taiji Suzuki Shin-ichi Ohta Osaka University / RIKEN AIP AI4Mathematicians: What do we want?
15:10-15:40 Break
15:40-16:20 Masaaki Imaizumi Masaaki Imaizumi The University of Tokyo / RIKEN AIP Mathematical Description on Principles of Deep Learning and AI: Precise Analysis of Dynamics via High-Dimensionality
16:20-17:00 Ayumi Igarashi Ayumi Igarashi The University of Tokyo / RIKEN AIP AI for collective decision making
Symposium Day 2: Thursday, August 20
Time Speaker Affiliation Title
9:30-10:30 Miranda Cheng  Miranda Cheng University of Amsterdam / Academia Sinica Institute of Mathematics / Simons Collaboration on Physics of Learning and Neural Computation Physics and Mathematics in the Age of AI
10:30-11:10  Yoh Tanimoto Yoh Tanimoto University of Rome Tor Vergata Formalising advanced mathematical definitions in Lean mathlib
11:10-11:30 Short Break
11:30-12:15  Yoh Tanimoto

Johan Commelin, Ken Ono, Shirley Ho, Masaaki Imaizumi

Panel Session
12:30-14:00 Poster Session + Lunch
14:00-15:00 Shirley Ho Shirley Ho Flatiron Institute / New York University / Polymathic AI TBA
16:40-17:20 Hitomi Yanaka Hitomi Yanaka The University of Tokyo / RIKEN AIP Exploring Compositional Meaning in Natural Language
15:10-15:40 Break
15:40-16:40 Johan Commelin Johan Commelin Mathlib Initiative / Utrecht University Building the Mathematical Commons
Symposium Day 3: Friday, August 21
Time Speaker Affiliation Title
9:30-10:30 Ken Ono Ken Ono Axiom Math / University of Virginia Mathematics in the Age of AI: Discovery, Formalization, and the Future of Proof
10:30-11:10 Akiyoshi Sannai Akiyoshi Sannai Kyoto University / Shiga University / RIKEN TRIP AI Math Referee: Verification, Autoformalization, and Beyond
11:10-11:30 Short Break
11:30-12:10 Takaharu Yaguchi Takaharu Yaguchi Kyushu University / RIKEN AIP Learning Geometric Structures in Physics
12:10-13:30 Poster Session  + Lunch
13:30-14:30 Sergei Gukov Sergei Gukov California Institute of Technology / Merkin Center for Pure and Applied Mathematics AI tools for long-horizon, sparse-reward tasks
14:30-15:10 Akiko Takeda Akiko Takeda The University of Tokyo / RIKEN AIP Mathematical Optimization in the Age of AI
15:10-15:40 Break
15:40-16:20 Shohei Shimizu Shohei Shimizu The University of Osaka / Shiga University / RIKEN AIP Toward Causal Scientific Discovery with AI
16:20-16:30 Motoko Kotani Motoko Kotani Director, RIKEN Pioneering Research Institute (PRI) Closing remarks
Poster Session

August 19 - 21 @Lunch Time


Number Presenter Affiliation Title
1 Suyog Garg The University of Tokyo Physics-Informed Encoder-Decoder Style Neural Networks for Modelling Time-Domain Gravitational Wave Signals
2 Yuki Goto Keio University / RIKEN AIP Data-Driven Structural Analysis of Integrable Hamiltonian Systems via Resonance Lattices
3 Anamaria Hell Kavli IPMU, The University of Tokyo LLMs for Algorithmic Theoretical Physics: Application to Degrees of Freedom and Beyond
4 Kotaro Kawasumi The University of Tokyo Computing Skeletal Data of Superfusion Categories with AI and Lean
5 Eren Mehmet Kiral RIKEN AIP Learning Parameter Distributions with Lie Groups
6 Julius Lohmann Institute of Science Tokyo Sparse BV Curves in the Wasserstein-1 Space
7 Risa Nii Kyushu University From Group Determinants to New Research Directions
8 Taketo Sano RIKEN iTHEMS Computations of Khovanov Homology
9 Leander Thiele Kavli IPMU, The University of Tokyo Machine Learning for Cosmological Inference
10 Andong Wang RIKEN AIP Robust Tensor Representation Learning
11 Takeru Yokota Osaka Institute of Technology Physics-Informed Neural Networks for Solving Functional Differential Equations

Venue

RIKEN Tokyo Campus

Nihonbashi 1-chome Mitsui Building (COREDO Nihonbashi), 15th floor,
1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan

Access map:
https://www.riken.jp/en/access/tokyo-map/index.html

RIKEN Tokyo Liaison Office

Speakers

Miranda Cheng

Miranda Cheng

University of Amsterdam Faculty of Science, Institute of Physics (ITF) / Academia Sinica Institute of Mathematics / Simons Collaboration on the physics of learning and neural computation

Johan Commelin

Johan Commelin

Director, Mathlib Initiative / Utrecht University Mathematical Institute

Michael Douglas

Michael R. Douglas

Senior Research Scientist, Center of Mathematical Sciences and Applications (CMSA), Harvard University / Simons Collaboration on Physics of Learning and Neural Computation / AletheAI, Inc.

Hal Finkel

Hal Finkel

Director (Acting), Computational Science Research and Partnerships (CSRP) Division, Office of Science, U.S. Department of Energy

Sergei Gukov

Sergei Gukov

John D. MacArthur Professor of Theoretical Physics and Mathematics, California Institute of Technology / Director, Merkin Center for Pure and Applied Mathematics

Shirley Ho

Shirley Ho

Group Leader, Cosmology X Data Science, CCA, Simons Foundation / Professor, Department of Physics and Center for Data Science, NYU / Principal Investigator, Polymathic AI

Ken Ono

Ken Ono

Mathematician, Axiom Math / Marvin Rosenblum Professor of Mathematics, University of Virginia

Ravi Vakil

Ravi Vakil

Robert Grimmett Professor of Mathematics, Stanford University / President, American Mathematical Society (AMS)

Ayumi Igarashi

Ayumi Igarashi

Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Masaaki Imaizumi

Masaaki Imaizumi

Associate Professor, Komaba Institute for Science, the University of Tokyo / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Shin-ichi Ohta

Shin-ichi Ohta

Professor, Department of Mathematics, Osaka University / Visiting Researcher, RIKEN Center for Advanced Intelligence Project (AIP)

Akiyoshi Sannai

Akiyoshi Sannai

Program-Specific Associate Professor, Department of physics, Kyoto University / Shiga University / RIKEN TRIP

Shohei Shimizu

Shohei Shimizu

Professor, SANKEN, The University of Osaka / Professor (Distinguished Professor) and Team Leader, Advanced Causal Inference Research Group, DSAI Center, Shiga University / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Taiji Suzuki

Taiji Suzuki

Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Akiko Takeda

Akiko Takeda

Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Yoh Tanimoto

Yoh Tanimoto

Professor (full), Department of Mathematics, Università di Roma “Tor Vergata”

Takaharu Yaguchi

Takaharu Yaguchi

Professor, Institute of Mathematics for Industry, Division of Advanced Mathematics Technology, Kyushu University / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Hitomi Yanaka

Hitomi Yanaka

Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo / Team Director, RIKEN Center for Advanced Intelligence Project (AIP)

Host

This international symposium is jointly hosted by RIKEN Pioneering Research Institute (PRI), RIKEN Center for Advanced Intelligence Project (AIP), and RIKEN Mathematical, Computational and Information Science Domain