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Intelligent Modeling Lab
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A lab that accelerates scientific discovery with simulation and AI.
AboutAbout the lab
Accelerating scientific discovery with simulation and artificial intelligence.
The Intelligent Modeling Lab studies how to understand natural and social phenomena through mathematical models and simulation.
The real world is complex, but the lab believes that extracting the key mechanisms and modeling them makes it easier to grasp the essence of a phenomenon.
The lab also works on using AI to make the research process more sophisticated, and is interested in mechanisms for collaboration between large language models (LLMs) and researchers.
The lab's website introduces it under the name Artificial Intelligence and Modeling Laboratory (AIML).
Key terms
- Large language model (LLM)
- An artificial intelligence that learns from large amounts of text and can read and write text.
- Tensor-train decomposition
- A method for compressing large multidimensional data by breaking it into a chain of small components.
- Surrogate model
- A lightweight approximate model used in place of a full-scale simulation that takes a long time to compute.
NewsLab news
View More ↗ResearchResearch themes
The lab aims to accelerate scientific discovery by combining mathematical models and simulation with artificial intelligence. Its research highlights include software development support, thermal design of 3D-ICs, modeling of wind turbine wakes, and compression of large-scale data.
*Illustrative imageSoftware Development Support with LLMs
The lab studies "Review Compass," a platform that uses LLMs to support a development workflow based on specification documents.
*Illustrative imageThermal Design of 3D-ICs
Using fast thermal simulation that can be applied early in the design process, the lab works on predicting where heat accumulates and optimizing cooling.
*Illustrative imageData-Driven Models of Wind Turbine Wakes
The lab works on representing wind turbine wakes, and the interactions between turbines in a wind farm, with surrogate models that use LLMs and genetic programming.
*Illustrative imageTensor-Train Decomposition for Compressing Large-Scale Data
To efficiently compress and analyze large amounts of multidimensional data, the lab works on tensor-train decomposition methods suited to parallel computation.
MembersFaculty
The members of the Intelligent Modeling Lab consist of faculty, PhD students, master's students, and undergraduate students.As of 2026
- ProfessorKenji Ono
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: “Geodesic grid MPAS ocean simulation vorticity 4096x4096” Jinrong Xie / CC BY-SA 4.0 (cropped)
- Software Development Support with LLMs: “SDLC - Software Development Life Cycle” Cliffydcw / CC BY-SA 3.0 (cropped)
- Thermal Design of 3D-ICs: “Pin fin heat sink with a z-clip” Dtc5341 / Public domain (cropped)
- Data-Driven Models of Wind Turbine Wakes: “Wind turbines, Wind farm, Wind power, Mirny, Crimea” Vyacheslav Argenberg / CC BY 4.0 (cropped)
- Tensor-Train Decomposition for Compressing Large-Scale Data: “Tensor tucker” Rama Hoetzlein (ramakarl) / CC BY-SA 4.0 (cropped)
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データマイニング・AI研究室): “Korean Robot” ApexInfinity Games / CC0 (cropped) - Related lab (文化知能科学研究室): “Anthem of Kamchatka Krai (orchestra and choir sheet music)” Lyrics: Boris Savvovich Dubrovin (ru) Music: Evgeniy Ivanovich Morozov (ru) / Public domain (cropped)
- Related lab (統計的学習研究室): “Bioinformatics Division, National Institute of Biotechnology (NIB) laboratory” Ishtiaquebioinfo / CC BY-SA 4.0 (cropped)
- Related lab (情報システムセキュリティ研究室): “IDF Enclosure for LAN and Switches” DoulosBen / CC BY 4.0 (cropped)
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