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Computational Mechanics Lab
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A computational mechanics lab that uses mathematics and computers to design the optimal shapes of objects.
AboutAbout the lab
Let's design the world through computation.
The Computational Mechanics Lab studies computational mechanics, which is grounded in mathematics, physics, and computer science.
It explores the foundations of analysis and design based on partial differential equations, and integrates them with AI and machine learning and with quantum computing.
With real-world applications and contributions to industry in mind, its top priority is building general-purpose, fundamental ideas and methodologies.
Key terms
- Partial differential equation
- An equation that describes relationships among quantities that vary with position and time, used to describe phenomena such as heat, flow, and deformation
- Boundary element method
- A numerical simulation method that solves equations by discretizing only the surface (boundary) of an object
- Topology optimization
- A design method that uses a computer to find the best structural shape for a given objective, including the number and placement of holes
ResearchResearch themes
Computational mechanics is a field in which mathematics, physics, and computer science are highly integrated, and it is expanding further with the rapid development of AI and machine learning and of quantum computing. The lab works on the boundary element method, shape and topology optimization, high-performance computing, AI and machine learning, and quantum computing.
*Illustrative imageAccelerating the Boundary Element Method
The lab develops fast algorithms, such as the fast multipole method, for the boundary element method. It focuses in particular on transient problems that change over time.
*Illustrative imageShape and Topology Optimization
The lab develops theory, numerical methods, and practical tools for optimizing the shape and topology of objects.
*Illustrative imageHigh-Performance Computing
The lab speeds up scientific and engineering computing software by using large-scale computing hardware.
*Illustrative imageAI and Machine Learning
The lab is opening up a new field at the intersection of conventional computational mechanics and data-driven methods.
MembersFaculty
The Computational Mechanics Lab consists of faculty members, secretaries, and doctoral, master's, and undergraduate students.As of 2026
- Associate ProfessorToru Takahashi
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Meshing in Finite Element Analysis” Abhiram vs 24 / CC BY-SA 4.0 (cropped)
- Accelerating the Boundary Element Method: “Surface waves” Roger McLassus / CC BY-SA 3.0 (cropped)
- Shape and Topology Optimization: “Material properties of metal powders for use in additive manufacturing ( )” National Institute of Standards and Technology / Public domain (cropped)
- High-Performance Computing: “The catalyst high performance computing (HPC)” ENERGY.GOV / Public domain (cropped)
- AI and Machine Learning: “Oak Ridge - Kraken (Cray XT5)” Daderot / Public domain (cropped)
- Related lab (Sensing Engineering Lab): “Atomic Force Microscope 01” Gannu03 / CC BY-SA 4.0 (cropped)
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- Related lab (Complex Fluid Engineering Lab): “Rheometer” Olivier Cleynen / CC BY-SA 4.0 (cropped)
- Related lab (Fluid System Engineering Lab): “Microfluidic Chip iX-factory” IX-factory STK / CC BY-SA 3.0 (cropped)
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