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Harada Lab
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The lab designs and applies artificial intelligence algorithms through optimization and machine learning.
AboutAbout the lab
Designing and applying AI through optimization and machine learning
The Harada Lab studies the design and application of artificial intelligence algorithms from two sides: optimization and machine learning.
In optimization, it works with algorithms based on evolutionary computation, which imitates the evolution and behavior of living organisms, including genetic algorithms and particle swarm optimization.
In machine learning, it targets a wide range of models, including deep learning and reinforcement learning.
Its main application areas are healthcare and social systems.
Key terms
- Evolutionary computation
- Evolutionary computation: a framework that imitates the evolution and behavior of living organisms. It includes genetic algorithms and particle swarm optimization.
- Optimization
- Optimization: finding optimal solutions to problems and using them for useful planning and design.
- Agent
- Agent: something equipped with machine learning capabilities. It is applied to concrete systems, and its characteristics are analyzed and controlled through simulation.
ResearchResearch themes
Aiming to design and apply intelligent systems with human-like intellectual abilities, the lab conducts research on optimization and machine learning. Its main application areas are healthcare and social systems.
*Illustrative imageAlgorithm Design for Optimization and Machine Learning
The lab studies the design and application of optimization algorithms based on evolutionary computation, which imitates the evolution and behavior of living organisms, such as genetic algorithms and particle swarm optimization. In machine learning, it targets a wide range of models, including deep learning and reinforcement learning.
*Illustrative imageApplying Optimization and Agents to Social Problems
The lab designs algorithms that solve concrete optimization problems in society, and uses the optimal solutions for planning and design. It applies agents equipped with machine learning capabilities to concrete systems, and analyzes their characteristics and controls them through simulation.
MembersFaculty
- ProfessorTaku Harada
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: “Obstacle avoidance robot car” Anani A. George / CC0 (cropped)
- Algorithm Design for Optimization and Machine Learning: “Murmuration 11-2025” Skander zarrad / CC BY-SA 4.0 (cropped)
- Applying Optimization and Agents to Social Problems: “Glasgow medical campus Simulation in Siafu” MiquelMartin / CC BY-SA 3.0 (cropped)
- Related lab (松澤研究室): “An UAV displayed by Vyomik drones at Amaravati Drone summit (02)” iMahesh / CC BY-SA 4.0 (cropped)
- Related lab (植松研究室): “Inside a card catalog at the Indiana State Library - ask the librarian” TBurmeister (WMF) / CC BY-SA 4.0 (cropped)
- Related lab (自然言語処理研究室): “Google server, circa 1999, Computer History Museum” The wub / CC BY-SA 4.0 (cropped)
- Related lab (滝本研究室): “Pam” Andreas Müller Fotografie / CC BY 4.0 (cropped)
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