Kyushu University Collaboration Team

Median-based estimators for randomized quasi-Monte Carlo integration

January 9 (Fri) 15:00 - 17:00, 2026

Kosuke Suzuki (Associate Professor, Yamagata University)

High-dimensional numerical integration is a ubiquitous challenge across various fields, from mathematical finance to computational physics and Bayesian statistics. While standard Monte Carlo (MC) methods are robust, their probabilistic error convergence rate of $O(N^{-1/2})$ is often insufficient for demanding applications. In this talk, I will introduce Quasi-Monte Carlo (QMC) and Randomized QMC (RQMC) methods, which offer a powerful framework for accelerating integration using low-discrepancy point sets. A key advantage of this deterministic approach is its ability to achieve a convergence rate of $O(N^{-1+\epsilon})$, significantly outperforming the standard MC rate. The second part of the talk will focus on the construction of point sets, specifically lattice rules and digital nets. I will explain how these methods achieve higher-order convergence rates, faster than $O(N^{-1})$, for sufficiently smooth integrands. I will also discuss their randomized variants and demonstrate how RQMC with mean-based estimators provides practical error estimation while maintaining high-order convergence. Finally, I will discuss recent progress in RQMC involving median-based estimators. I will highlight how these estimators achieve almost optimal convergence rates for various function spaces without requiring prior knowledge of the integrand.

Venue: Hybrid Format (3F #359 and Zoom), Seminar Room #359

Event Official Language: English

Topological Image Analysis

December 25 (Thu) 12:00 - 13:00, 2025

Shizuo Kaji (Professor, Institute of Mathematics for Industry, Kyushu University / Professor, Center for Science Adventure and Collaborative Research Advancement (SACRA), Graduate School of Science, Kyoto University)

Topological Data Analysis (TDA) applies algebraic topology to the study of data such as point clouds. When applied to image and volumetric data, TDA provides a way to capture the topological features that characterise shapes and spatial structures. In this talk, I will outline the strengths and limitations of TDA for image analysis, and compare its capabilities with those of deep neural networks. I will also present hands-on examples using our open-source software Cubical Ripser. Finally, I will highlight a new direction in the use of TDA for image processing.

Venue: Room C501, West Zone 1 Building D, Ito Campus, Kyushu University, SUURI-COOL (Kyushu) (Main Venue) / via Zoom

Event Official Language: English

Rational function semifields of dimension one

November 7 (Fri) 13:30 - 15:30, 2025

JuAe Song (Assistant Professor, Faculty of Mathematics, Kyushu University)

Recently some researchers gave many studies toward algebro-geometric foundation for tropical geometry. I focused on rational function semifields of tropical curves and characterized them. With this characterization, in this talk, I suggest a definition of ``rational function semifield of dimension one". This definition can write out weight in the term of $\boldsymbol{T}$-algebra homomorphism, and can write balancing condition together with harmonic functions, where both weight and balancing condition are fundamental concepts for tropical varieties and $\boldsymbol{T}$ is the tropical semifield $(\boldsymbol{R} \cup \{-\infty\}, \operatorname{max}, +)$.

Venue: Seminar Room #359 / via Zoom

Event Official Language: Japanese

Introduction to Lean theorem prover

October 31 (Fri) 14:00 - 17:00, 2025

Yuma Mizuno (Postdoctoral Researcher, University College Cork, Ireland)

A theorem prover is a tool for the formalization of mathematics, that is, for rigorously expressing and verifying theorems and proofs on a computer. In recent years, the Lean theorem prover has seen progress in the formalization of a wide range of areas of mathematics. In this talk, I will explain formalization of mathematics in Lean from the basics and survey the formalized results achieved to date.

Venue: via Zoom / #359, Seminar Room #359

Event Official Language: English

Computer Algebra with Deep Learning

September 5 (Fri) 15:00 - 17:00, 2025

Yuki Ishihara (Assistant Professor, Department of Mathematics, College and Science Technology, Nihon University)

Computer algebra is a field that aims to perform various mathematical calculations on computers. In recent years, there has been a surge in efforts to accelerate computer algebra algorithms using deep learning models such as “Transformer,” which is used in ChatGPT. In this lecture, I will introduce the results of joint research with Professor Kera et al. on learning Gröbner bases with Transformer.

Venue: via Zoom / #359, Seminar Room #359

Event Official Language: English

Crossroads of Virology and Mathematical Sciences

August 8 (Fri) 9:30 - 17:30, 2025

Makoto Takeda (Professor, Graduate School of Medicine, The University of Tokyo)
Yasuyuki Yamaji (Professor, Graduate School of Agricultural and Life Sciences, The University of Tokyo)
Kotaro Kiga (Director, Japan Institute for Helth Security)
Daishi Fujita (Associate Professor, Kyoto University Institute for Advanced Study (KUIAS))
Miyuki Koiso (Professor Emeritus, Kyushu University)
Daisuke Kuroda (Associate Professor, Department of Biosciences, College of Humanities and Sciences, Nihon University)
Catherine Beauchemin (Deputy Director, RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS))
Shinichi Tanigawa (Associate Professor, Graduate School of Information Science and Technology, The University of Tokyo)
Takao Hashiguchi (Professor, Institute for Life And Medical Sciences, Kyoto University)
Hideo Fukuhara (Associate Professor, International Institute for Zoonosis Control, Hokkaido University)
Shohei Kojima (Special Postdoctoral Researcher, Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences (IMS))
Shuhei Miyashita (Assistant Professor, Graduate School of Agricultural Science, Tohoku University)
Ryoko Oishi-Tomiyasu (Professor, Institute of Mathematics for Industry, Kyushu University)
Suzuki Yuta (Principal Investigator, Japan Science and Technology Agency (JST))
Adnan Sljoka (Research Scientist, Molecular Informatics Team, RIKEN Center for Advanced Intelligence Project (AIP))

By creating a shared space for dialogue, we aim to stimulate new research directions and foster collaborative insights through the integration of mathematical sciences into studies of both the structural principles that govern viral form and function, and the dynamics of viral replication. We invite participation from both mathematical and theoretical scientists interested in the structure and replication mechanisms of viruses, as well as virologists who are open to exploring the potential of mathematical abstraction. Program: Morning Session I (Viruses) 10:00–10:20 Measles virus engineering Makoto Takeda (The University of Tokyo, Graduate School of Medicine) 10:20–10:40 Plant immunity to potexviruses Yasuyuki Yamaji (The University of Tokyo, Graduate School of Agricultural and Life Sciences) 10:40–11:00 Sophisticated phage infection strategies and bacterial defense responses Kotaro Kiga (National Institute of Infectious Diseases) Break (11:00–11:15) Morning Session II (Molecules, Math) 11:15–11:35 Designing Polyhedral Molecular Architectures at Will Daishi Fujita (Kyoto University, Institute for Advanced Study) 11:35–11:55 Anisotropic energy and (curved) polyhedron Miyuki Koiso (Kyushu University) 11:55–12:15 Nature-Inspired Design of Two-Component Protein Assemblies: From Cytoskeleton-Like to Virus-Like Structures Yuta Suzuki (JST PRESTO) Lunch Break (12:15–13:20) Afternoon Session I (Comp Sci, Math) 13:20–13:40 Computer-aided antibody design Daisuke Kuroda (Nihon University, Department of Life Sciences) 13:40–14:00 Revealing Protein Allostery and Functional Dynamics via Rigidity Theory and NMR Adnan Sljoka（RIKEN AIP） 14:00–14:20 Using mathematical models to identify experimental pitfalls when probing virus replication in vitro Catherine Beauchemin (RIKEN iTHEMS) 14:20–14:40 Combinatorics behind statics and flexibility of graphs Shinichi Tanigawa (The University of Tokyo, Graduate School of Information Science and Technology) Break (14:40–14:55) Afternoon Session II (Structures) 14:55–15:15 Glycoprotein structures in human pathogenic RNA viruses Takao Hashiguchi (Kyoto University, Graduate School of Medicine and Biomedical Sciences) 15:15–15:35 Introduction of cryo-electron microscopy facilities at Hokkaido University Hideo Fukuhara (Hokkaido University, Research Center for Zoonosis Control) Break (15:35–15:50) Afternoon Session III (Viruses, Math) 15:50–16:10 Human genetics during virus infection Shohei Kojima (Keio University, Bio2Q) 16:10–16:30 Suicidal population resistance of land plants against viruses Shuhei Miyashita (Tohoku University, Graduate School of Agricultural Science) 16:30–16:50 Mathematical and crystallographic perspectives in virology Ryoko Tomiyasu (Kyushu University, IMI) Organizers: Catherine Beauchemin (RIKEN iTHEMS) Makoto Takeda (University of Tokyo, Graduate School of Medicine) Ryoko Tomiyasu (Kyushu University, IMI)

Venue: #359, 3F, Main Research Building (Main Venue) / via Zoom

LeanConjecturer: Automatic Generation of Mathematical Conjectures for Theorem Proving

August 1 (Fri) 16:00 - 18:00, 2025

Naoto Onda (Project Research Engineer, Research Administrative Division, Omron Sinic X Corporation)

We introduce LeanConjecturer, a pipeline for automatically generating university-level mathematical conjectures in Lean 4 using Large Language Models (LLMs). Our hybrid approach combines rule-based context extraction with LLM-based theorem statement generation, addressing the data scarcity challenge in formal theorem proving. Through iterative generation and evaluation, LeanConjecturer produced 12,289 conjectures from 40 Mathlib seed files, with 3,776 identified as syntactically valid and non-trivial, that is, cannot be proven by aesop tactic. We demonstrate the utility of these generated conjectures for reinforcement learning through Group Relative Policy Optimization (GRPO), showing that targeted training on domain-specific conjectures can enhance theorem proving capabilities. Our approach generates 103.25 novel conjectures per seed file on average, providing a scalable solution for creating training data for theorem proving systems. Our system successfully verified several non-trivial theorems in topology, including properties of semi-open, alpha-open, and pre-open sets, demonstrating its potential for mathematical discovery beyond simple variations of existing results.

Venue: via Zoom / #359, Seminar Room #359

Event Official Language: English

Modeling form growth in curved spaces using Riemannian L-systems

July 17 (Thu) 16:00 - 17:30, 2025

Christophe Godin (Research Derector, Inria, Univ Lyon, France)

In the past 50 years, the formalism of L-systems has been successfully used and developed to model the growth of filamentous and branching biological forms. These simulations take place in classical 2-D or 3-D Euclidean spaces. However, various biological forms actually grow in curved, non-Euclidean, spaces. This is for example the case of vein networks growing within curved leaf blades, of unicellular filaments, such as pollen tubes, growing on curved surfaces to fertilize distant ovules, of teeth patterns growing on folded epithelia of animals, of diffusion of chemical or mechanical signals at the surface of plant or animal tissues, etc. In this talk, I will describe how we extended the formalism of L-systems to model the growth of branching structures in curved spaces. We will discuss how the space may feedback on the growing form and contribute to shape. I will also look at examples, where the space in which the form is growing is not necessarily a surface embedded in the euclidean 3-dimensional space, but is rather a space intrinsically curved, i.e. curved but not embedded in any higher-dimensional space. The possibility to use these more abstract Riemannian spaces potentially opens new avenues for formalizing rules driving the morphogenesis of living forms.

Venue: via Zoom / SUURI-COOL (Kyushu)

Event Official Language: English

Quantum Computing Algorithms and Institute of Mathematics-for-Industry

July 3 (Thu) 15:30 - 17:00, 2025

Hiroyuki Ochiai (Professor, Institute of Mathematics for Industry, Kyushu University)

This is the kickoff talk of the Kyushu University Collaboration Team, which aims to foster communication between iTHEMS and IMI. I will introduce some of IMI's activities and organization, as well as my own work, including research on quantum algorithms that began with the launch of the Quantum Computing System Center in 2022.

Venue: #345-347, 3F, Main Research Building

Event Official Language: English