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Zettsu Lab
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A lab studying AI orchestration, which coordinates multiple AIs and data.
AboutAbout the lab
Connecting people, things, and events with AI.
The Zettsu Lab studies AI orchestration, a technology that solves problems by coordinating multiple AI models and data.
AI orchestration is a technology that selects appropriate AI and data according to the task and real-world situation, and keeps improving processing and models while evaluating results.
By combining LLMs, multimodal AI, predictive models, databases, edge AI, and more, the lab aims to achieve recognition, reasoning, decision-making, and service provision that are difficult for a single AI to handle.
Key terms
- AI orchestration
- Technology that selects and coordinates appropriate AI and data according to the task and situation, and keeps improving processing and models while evaluating results
- Physical AI
- AI that operates in the real world, such as in autonomous driving and robots
- Multimodal AI
- AI that handles multiple types of data together, such as video, audio, text, and sensor data
NewsLab news
A paper by Professor Zettsu and colleagues was published in Safety Science
A paper by Professor Zettsu and colleagues was published in International Journal of Data Science and Analytics
A paper by Professor Zettsu and colleagues was published in Scientific reports
ResearchResearch themes
The lab studies AI orchestration technology, which coordinates multiple AI models, databases, external services, computing resources, and human knowledge according to purpose. It aims to achieve recognition, reasoning, decision-making, and service provision that are difficult for a single AI to handle.
*Illustrative imageSafe action support for LLMs and physical AI
Action candidates generated by physical AI are verified by an LLM and external evaluators, corrected or replanned if necessary, and left to a human's judgment. The research aims to suppress dangerous behavior of AI operating in the real world, such as autonomous driving and robots.
*Illustrative imageAI agents supporting development process design
The lab studies AI agents that break ambiguous natural-language requirements down step by step and organize them, supporting requirements definition, the design of development processes, and content generation. In areas such as game development, it designs the roles and execution order of multiple agents.
*Illustrative imageDialogue understanding and hypothesis generation through LLM coordination
By coordinating LLM generation with multifaceted evaluation, the lab extracts contextual information and causal relationships from multi-turn exchanges that contain uncertainty. Applications include generating causal hypotheses from dialogue logs and generating responses that match the user's intent.
*Illustrative imageMultimodal AI model coordination
The lab builds recognition and prediction models by combining pretrained models for each type of data, such as video, audio, text, and sensor data. It applies them to areas such as near-miss prediction while driving, integrating dashcam video, heart rate, and in-vehicle environment sensors.
MembersFaculty
The members of the Zettsu Lab are faculty, master's students, and undergraduate students.As of 2026
- ProfessorKoji Zettsu
- Project Assistant ProfessorCHEN Caijuan
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: “Man with smartphone and laptop (Unsplash)” Alejandro Escamilla alejandroescamilla / CC0 (cropped)
- Safe action support for LLMs and physical AI: “Роботска рака (2)” Луната1999 / CC BY-SA 4.0 (cropped)
- AI agents supporting development process design: “Flowchart of a code health checker program” Ddefeat / CC0 (cropped)
- Dialogue understanding and hypothesis generation through LLM coordination: “Woman with long nails typing on a laptop keyboard” Shixart1985 / CC BY 2.0 (cropped)
- Multimodal AI model coordination: “Vintage car interior shows classic steering wheel and dashboard details in a garage setting” Shixart1985 / CC BY 2.0 (cropped)
- Related lab (Ishikawa Lab (Database Systems Group)): “Cabinet Network Rear Close” Robert.Harker / CC BY-SA 3.0 (cropped)
- Related lab (Sasano Lab): “QWERTY keyboard” MichaelMaggs / CC BY-SA 3.0 (cropped)
- Related lab (Toyama Lab): “Ghalib Law Library Books on the shelve” Iliaswiki23 / CC BY-SA 4.0 (cropped)
- Related lab (Kudo Lab): “Central Projection Idealised Camera Model” Olaf Peters (OlafTheScientist) / CC BY-SA 4.0 (cropped)
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