Labs in Kyushu University, Institute of Mathematics for Industry, Division of Liaison Strategy

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〈科学技術・イノベーション政策〉 (introduction coming soon)

Science, technology, and innovation policy; industry–academia collaboration; standards and certification; promoting applications of the mathematical sciences and building frameworks for industry–academia collaboration

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A lab that uses dynamical systems and verified numerical computation to uncover the singular behavior of differential equations.

The lab of Professor Kaname Matsue studies applied mathematics, grounded in dynamical systems theory, differential equations, and numerical analysis. Its basic spirit is to unravel the fundamental properties of the "strange" or "singular" behavior hidden in phenomena generated by differential equations and the like. With applied mathematics at its core, the lab also tackles problems arising from combustion and related energy issues.

#Finite-time singularities #Verified numerical computation #Dynamical systems

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The lab studies machine learning and explainable AI.

Professor Akihiro Yamaguchi's research themes are machine learning, explainable AI (XAI), interpretability, and time-series data mining. The lab studies methods that make the decisions of AI systems that classify time-series data interpretable to humans. The professor belongs to the Liaison Strategy Division at the Institute of Mathematics for Industry, Kyushu University.

#Explainable AI #Machine learning #Time series data mining

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The lab studies social mathematics, using mathematical optimization and game theory to design social systems and policies.

Associate Professor Akifumi Kira specializes in mathematical optimization and studies problems that require repeated decision-making and problems that involve uncertainty. The lab works on the theory and applications of dynamic programming, a method for solving such problems efficiently. It also works on social mathematics: research that uses mathematical techniques such as optimization and game theory to design fair systems and policies that people find acceptable. The lab has developed technology in collaboration with people on the front lines of challenges such as logistics and the allocation of places at daycare centers.

#Mathematical social science #Dynamic programming #Ride-sharing matching

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The lab studies numerical methods for partial differential equations and their errors.

Associate Professor Daisuke Tagami's fields are applied mathematics and computational mechanics, and his research focuses on developing numerical methods for partial differential equations, error estimation, and applications to real-world problems. The lab's subjects include numerical analysis of particle methods, large-scale numerical methods for electromagnetic field problems, viscoelastic flow problems, moving boundary problems, the Navier–Stokes equations, and thermal convection problems. The lab also studies applications of the Navier–Stokes equations to the numerical computation of drag and lift, and applications of thermal convection problems to the numerical computation of glass melting.

#Numerical analysis #Particle methods #Finite element method

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This is the lab of Professor Fumikazu Sato at the Institute of Mathematics for Industry.

Professor Fumikazu Sato is a Professor in the Liaison Strategy Division of the Institute of Mathematics for Industry. Professor Sato also holds a concurrent faculty appointment in the Department of Mathematics, Faculty of Science. As a social contribution activity, Professor Sato serves as a technical advisor (research guidance) to companies.

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The lab explores the singular behavior of differential equations through dynamical systems theory and numerical computation.

The Matsue Lab studies the properties of "strange" and "singular" behavior that arises in differential equations, using dynamical systems theory and numerical analysis. The research is grounded in applied mathematics: dynamical systems theory, differential equations, and numerical analysis (especially verified numerical computation). The lab focuses mainly on finite-time singularities, such as solutions of differential equations blowing up in finite time, and also tackles problems that originate in combustion and energy issues. Prof. Matsue also serves as a WPI Professor at the International Institute for Carbon-Neutral Energy Research at Kyushu University.

#Dynamical systems #Verified numerical computation #Finite-time singularities

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The lab works on making AI that classifies time series data interpretable.

Prof. Yamaguchi lists explainable AI (XAI), interpretability, machine learning, and time series data mining as research topics. Prof. Yamaguchi is a Professor in the Liaison Strategy Division at the Institute of Mathematics for Industry, Kyushu University. In the papers listed in the researcher profile, the work deals with AI that classifies time series data, and with methods that let people interpret trained classifiers.

#Explainable AI (XAI) #Machine learning #Time series data mining

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The lab studies social mathematics, using mathematical optimization to design the mechanisms of society.

Associate Professor Kira's lab specializes in mathematical optimization and studies the theory of dynamic programming and its applications. The lab is interested in problems that require repeated decision-making and problems that involve uncertainty. It also works on social mathematics, which uses mathematical techniques such as optimization and game theory to design fair and widely accepted systems and policies. Associate Professor Kira has developed technologies in collaboration with practitioners in the field, for example on childcare center admission allocation and joint transportation matching.

#Mathematical social science #Mathematical optimization #Dynamic programming

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The lab mathematically investigates numerical methods for partial differential equations.

Associate Professor Daisuke Tagami's lab works in applied mathematics and computational mechanics. The lab is interested in developing methods for solving partial differential equations numerically, estimating their errors, and applying them to real-world problems. Specifically, it works on numerical analysis of particle methods, building large-scale numerical methods for electromagnetic field problems, and numerical analysis of viscoelastic flow problems.

#Numerical analysis #Particle methods #Error analysis