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451 labs · 366 student voices
Faculties at The University of Tokyo ›
Takuya Katashima, Lecturer
Materials & Nanotech0 student voices
The Katashima-Chung Lab studies biomaterials, with the rheology of soft matter as its core technique. Soft matter, such as food and cosmetics, is a class of materials with properties between those of a solid and a liquid. Human body tissues have similar properties, so designing materials that come into contact with the body requires understanding and controlling how they deform and flow. The lab aims to establish "molecular kansei engineering," a field that numerically evaluates people's sensory needs for materials (kansei, or human sensibility) and designs materials from the molecular level.
Hiroyuki Matsuura, Professor
Materials & Nanotech0 student voices
The Matsuura Lab studies "high-temperature processes," which handle materials in large quantities at high temperatures. High-temperature processes are used in many areas of industry, including metal manufacturing, ceramics, and cement. Focusing on processes for producing steel and nonferrous metals and processes for reusing resources, the lab develops methods that are efficient and place a small burden on the environment. The lab places importance on creating a flow in which materials circulate smoothly through society, so as not to leave a negative legacy for the next generation.
Takeo Hoshino, Project Professor
Environment & Sustainability0 student voices
Hoshino Lab studies the flow in which foundational materials such as iron, aluminum, and copper are produced, used, discarded, and recycled in society. The lab develops methods to analyze and evaluate environmental burden and resource issues across the life cycle of materials. It also predicts the impurities that accumulate through recycling, and which metals may face shortages in a decarbonized society. The lab aims to connect its research results to advice for industry and to policy recommendations.
Yukihiro Shimogaki, Professor
Semiconductors & Electronic Devices0 student voices
The Shimogaki Lab studies thin-film deposition processes, which form thin films on the surfaces of objects. Materials research is not only about creating new substances; it is also deeply tied to how they are made, that is, the process. The lab analyzes the mechanisms by which films form to bring out the full potential of the process, and adds new mechanisms to make the process itself more advanced. The lab works on semiconductor interconnects, next-generation aerospace materials, and coatings for cutting tools.
Yasushi Shibuta, Professor
Materials & Nanotech0 student voices
Materials Modelling Lab (Shibuta Lab) studies how materials form and what properties they have, using computer simulation. Centered on molecular dynamics, which calculates the motion of each individual atom, the lab investigates phenomena such as how liquid metal solidifies. The lab also carries out large-scale calculations on supercomputers and develops new methods that combine simulation with machine learning. In addition, the lab studies how to understand life-like phenomena using the concepts of artificial life.
Takamasa Tsukamoto, Lecturer
Materials & Nanotech0 student voices
The Tsukamoto Lab studies the synthesis and properties of extremely small chemical substances known as "quantum-sized materials." Quantum-sized materials are about the size of a cluster of a few to a few dozen atoms, and they have the potential to become the materials of the future. On the other hand, a major challenge is that it is difficult to synthesize and design them as intended. From both experimental and theoretical sides, the lab independently develops new synthesis techniques and design theories.
Wan Yi, Lecturer
Materials & Nanotech0 student voices
Wan Lab conducts research on evaluating and controlling the properties of advanced composite materials so that they can actually be used in society. The lab pursues its research not only from the perspective of materials engineering but also with an eye to how the results can benefit the society of the future. Using X-ray CT and statistical methods, the lab investigates the relationship between the internal fiber structure and the properties of carbon fiber reinforced composites. The lab also carries out extensive international collaborative research, and supervises students jointly with the Takahashi Lab.
Ryota Wada, Professor
Environment & Sustainability0 student voices
Wada Lab conducts research that uses engineering and data science to solve challenges in industries set in the ocean (ocean industries). Its subjects include offshore wind power, offshore CCS, methane hydrate development, and the Arctic Sea Route. Because wave periods and wind strength at sea cannot be known in advance, the lab examines this "uncertainty" and the associated risks from a variety of perspectives. Working together with experts and stakeholders, the lab proposes systems and concepts that can actually be used in society.
Kazuo Yonekura, Associate Professor
AI & Machine Learning0 student voices
The Yonekura Lab pursues the fusion of mathematics and engineering, aiming to solve engineering problems with the power of mathematics. Using machine learning such as generative models and reinforcement learning, the lab takes on the challenge of innovating the design of mechanical products. The lab regards theory and application as the two wheels of its research, and places particular importance on industrial applications. The lab holds lab seminars and other activities jointly with the Suzuki Lab.
Tomonori Yamada, Associate Professor
Software & Computing0 student voices
The Yamada Lab studies simulation of engineered systems from the standpoint of computational science. Engineered systems created to enrich people's lives sometimes cause problems that were not anticipated at the design stage, such as large-scale disasters and environmental burdens. The lab conducts research and development to predict such problems with advanced simulation and to overcome them. Its core technologies are high-performance computing, multiphysics simulation, and machine learning on simulation result data.
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