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27 labs · 0 student voices
Other departments in Faculty of Engineering Science ›Faculties at The University of Osaka ›
Takayuki Kobayashi, Professor
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The Differential Equations Group (Kobayashi Lab) seeks to understand natural and social phenomena through mathematical models such as differential equations, and studies the properties of their solutions using mathematical methods. By reducing phenomena to pure mathematics, the lab also aims to deepen mathematics itself. The lab also uses computer-assisted analysis to study the qualitative and global properties of solutions to differential equations. The lab belongs to the Mathematical Modeling Division of the Mathematical Science Area in the Department of Systems Innovation, Graduate School of Engineering Science.
Michinori Ishiwata, Professor
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The Applied Analysis Lab studies mathematical models, which express phenomena seen in nature and society as equations, by analyzing them with mathematical methods. Its subjects are wide-ranging, including chemical reactions, fluid motion, the behavior of quantum-mechanical particles, and the progression of malignant tumors. On the theoretical side, the lab investigates the properties of the partial differential equations obtained as models of phenomena, using methods of modern mathematics such as the calculus of variations, dynamical systems theory, and blow-up analysis. On the applied side, the lab examines the properties of the equations through numerical simulation and compares the results with actual phenomena to verify the validity of the models.
Yoshikazu Terada, Professor
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The Statistical Analysis Group (Terada Lab) is grounded in mathematical statistics and conducts research aimed at both a mathematical understanding of modern data analysis methods and their application to real-world problems. The lab emphasizes not only learning how to use data analysis methods, but also understanding why a method is effective and what its limitations are, so that students gain the expertise to use these methods well. The lab was newly launched in April 2026.
Tomoyuki Sugimoto, Professor
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The Data Science Research Group develops statistical methods and machine learning methods that derive new knowledge from multivariate data, and studies their mathematical statistics and learning theory. Built on a foundation of mathematical statistics, the lab works on causal inference, machine learning, analysis of medical and health data, survival analysis, meta-analysis, and more. It considers what can be concluded, and how far, when data are incomplete, as with missing data and censoring. On the lab's website, it is introduced under the name "Sugimoto Lab".
Masayuki Uchida, Professor
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The Statistical Inference and Decision Group (Uchida Lab) conducts research and education on statistical inference for stochastic process models. Combining mathematical statistics with computer-based theoretical statistics, the lab works to elucidate phenomena described by stochastic process models based on data. Statistical inference for stochastic process models is applied to financial data analysis, actuarial statistics for insurance, statistical seismology, and more. The lab belongs to the Mathematical and Quantitative Finance Chair in the Social Systems Mathematics Area of the Department of Systems Innovation, Graduate School of Engineering Science.
Jun Sekine, Professor
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On the website of the Sekine-Fukasawa-Yano Lab, the Stochastic Models in Finance Lab is introduced as the Financial Mathematical Models Research Group (Sekine Lab). The Sekine-Fukasawa-Yano Lab conducts research and education centered on mathematical finance and stochastic analysis. The website also lists research groups in stochastic analysis (Fukasawa Lab) and the theory of stochastic processes (Yano Lab). The lab belongs to the Mathematical Science Course in the Department of Information and Computer Sciences, School of Engineering Science, Osaka University, and to the Social Systems Mathematics Area in the Department of Systems Innovation, Graduate School of Engineering Science.
Masaaki Fukasawa, Professor
0 student voices
The Stochastic Analysis Lab shares a single website under the name Sekine-Fukasawa-Yano Lab, and corresponds to the Fukasawa lab within it. On the website, the Sekine-Fukasawa-Yano Lab is described as conducting research and education centered on mathematical finance and stochastic analysis. The department's introduction lists stochastic integrals, stochastic differential equations, fractional Brownian motion, rough path analysis, stochastic numerical analysis, and decentralized finance as keywords. At the graduate level, the lab belongs to the Division of Mathematical Science for Social Systems, and at the undergraduate level, to the Mathematical Science Course of the Department of Information and Computer Sciences.
Yuko Yano, Professor
0 student voices
The stochastic processes research group is the Yano lab within the Sekine-Fukasawa-Yano Lab. On the lab's website, the Sekine-Fukasawa-Yano Lab is described as conducting research and education centered on mathematical finance and stochastic analysis. At the undergraduate level, the lab belongs to the Mathematical Science Course of the Department of Information and Computer Sciences in the School of Engineering Science, and at the graduate level, to the Division of Mathematical Science for Social Systems in the Department of Systems Innovation of the Graduate School of Engineering Science.
Takanori Isobe, Professor
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The Isobe Lab studies next-generation security foundations with cryptography at its core. The lab advances the design of cryptography and the security evaluation of cryptographic systems in actual use, from both theoretical and implementation perspectives. With the goal of putting research results into practice in society, the lab collaborates with industry, standardization bodies, and the open-source software (OSS) community. Each student has an independent research theme and advances it through discussions with their advisors and fellow researchers.
Naoki Wakamiya, Professor
0 student voices
The Wakamiya Lab studies new information and communication technologies by learning from the mechanisms of living organisms. Information and communication systems grow larger and more complex every year, and unexpected situations can cause their performance to drop drastically or stop altogether. The lab therefore works on Bio-ICT, which applies the highly scalable, adaptable, and robust mechanisms of living organisms to information and communication technology. Rather than imitating the outward structure or behavior of organisms, the lab takes the mathematical models behind them as its object of study.
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