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Harmonious Systems Engineering Lab
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A lab that brings artificial intelligence to society to improve people's lives.
AboutAbout the lab
AI for harmony between people and society.
The Harmonious Systems Engineering Lab aims to contribute to people's happiness and social harmony by applying artificial intelligence technology.
Its fields are broad, including deep learning, machine learning, genetic algorithms, game theory, and multi-agent systems.
The lab implements these as smartphone, cloud, and web services, and carries its research through to having people in the real world use them.
As an extension of this, venture companies have emerged from its research results, and joint research with companies is progressing.
Key terms
- Deep learning
- A machine learning method in which a neural network with many stacked layers is trained on a large number of examples so that it learns to capture features
- Multi-agent system
- A mechanism that combines multiple entities that make their own decisions and act, so that they work well as a whole
- Large language model
- Artificial intelligence that learns how words fit together from a large amount of text, enabling it to read and write sentences
NewsLab news
Paper accepted to Sensors and Materials
A doctoral student received the Research Presentation Encouragement Award at the 29th Research Presentation Meeting of the Society for Tourism Informatics
A master's student received the Excellence Award at the 39th Annual Conference of the Japanese Society for Artificial Intelligence
A master's student received the Best Oral Presentation Award at the International Conference on Innovation in Artificial Intelligence
A master's student received the Best Student Paper Award at KICSS2024
ResearchResearch themes
The lab studies technologies important for realizing artificial intelligence, such as deep learning, evolutionary computation, and game theory. It also works concretely on applications to social systems, service development, and tourism informatics.
*Illustrative imageTurning Clothing Designs into Reality with Image-Generating AI
The lab builds a system that gradually makes the clothing design a user has in mind more concrete through dialogue, and creates fashion images.
*Illustrative imageCaption Generation for Clothing Image Pairs
The system compares images of two similar garments and automatically generates a caption that describes the differences between them, emphasizing those differences.
*Illustrative imageA Support System for Deciding Snow Removal Dispatch
This is joint research with Horiguchi-gumi Co., Ltd. The lab is building a site for sharing road snow removal information, aiming to solve the difficulty of deciding whether to dispatch crews and the danger of patrols to check snow conditions.
*Illustrative imageImproving Text with Large Language Models
In joint research with YAMAGATA Corporation, the lab is developing a system that automatically rewrites text written by non-experts into more readable text.
MembersFaculty
The members of the Harmonious Systems Engineering Lab consist of faculty members, students in the doctoral, master's, and undergraduate programs, and a secretary.As of 2026
- ProfessorHidenori Kawamura
- Associate ProfessorTomohisa Yamashita
- Assistant ProfessorSoichiro Yokoyama
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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: “Snow removal in Sapporo ( )” MIKI Yoshihito / CC BY 2.0 (cropped)
- Turning Clothing Designs into Reality with Image-Generating AI: “Interior sports clothing store Cala Millor” Steffen Mokosch / CC BY-SA 4.0 (cropped)
- Caption Generation for Clothing Image Pairs: “Mannequins in Galeries de la Capitale 3” Wilfredor / CC BY-SA 4.0 (cropped)
- A Support System for Deciding Snow Removal Dispatch: “VTrans snow plow truck VT Rte 114 East Haven VT February 2019” Artaxerxes / CC BY-SA 4.0 (cropped)
- Improving Text with Large Language Models: “Aufgeschlagenes Buch” Dietmar Rabich / CC BY-SA 4.0 (cropped)
- Related lab (自律系工学研究室): “Kilobot robot swarm” asuscreative / CC BY-SA 4.0 (cropped)
- Related lab (知能ソフトウェア研究室): “Yujing Line expressway and Provincial Highway at midnight” Guanting Chen / CC BY-SA 4.0 (cropped)
- Related lab (知能情報学研究室): “Quiet Electric Engine V1 (QUEEN V1) Experiment (GRC-2024-C-06530)” NASA Glenn Research Center / NASA/GRC/Sara Lowthian-Hanna / Public domain (cropped)
- Related lab (メディアダイナミクス研究室): “Aperture grille closeup” Selçuk Oral (drumex) / CC BY-SA 3.0 (cropped)
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