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Hasegawa Lab
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A lab that builds computers that learn like a brain, using the movement of ions.
AboutAbout the lab
Material intelligence for an information society aligned with the SDGs
Hasegawa Lab researches the development of brain-like computers that become smarter on their own.
The lab builds "brain-inspired devices (atomic switches)" that use the mechanism by which ions move within a material and cause redox reactions.
It also searches for new physicochemical phenomena that occur on the surface and inside of solids, and works to clarify their mechanisms.
The lab also carries out research and development toward familiar applications, such as image processing and the processing of sound and light signals.
Key terms
- Atomic switch
- A device that switches on and off using the movement of ions and redox reactions within a material
- Reservoir computing
- A next-generation brain-inspired information processing method that uses the complex responses of a material itself for computation
- Redox reaction
- A chemical reaction in which substances exchange electrons and their properties change
NewsLab news
Mixed electron-ion conduction improves material reservoir performance
Applications now open for lab visits ahead of undergraduate thesis lab assignment
A master's student wins a paper award at an international conference
A master's student wins the Miyabe Award
A master's student's paper is published in an academic journal
ResearchResearch themes
The lab searches for new physicochemical phenomena that occur on the surface and inside of solids, and works to clarify their mechanisms. In particular, it focuses on developing brain-inspired devices and brain-inspired information processing systems that use ion migration and redox reactions.
*Illustrative imageRock-paper-scissors with AI
The lab developed a system in which a human and an AI play rock-paper-scissors by processing images of the hand captured by a camera. The AI makes its move after the human, but achieves a high win rate.
*Illustrative imageIn-sensor computing
The lab demonstrated a physical reservoir that can directly process environmental signals such as light and sound, without first converting them into voltages with a camera or similar device. It is expected to be applied to edge computing.
*Illustrative imageHandwritten character recognition
Using a physical reservoir based on ion migration, the lab tackled the task of recognizing handwritten characters and achieved performance nearly equal to that of software.
*Illustrative imagePhysical reservoir using ion migration
Using the internal electric fields created by ions moving within a material, the lab realizes the functions required for reservoir computing, which is expected to be a next-generation brain-inspired information processing system.
MembersFaculty
The members of Hasegawa Lab are the professor and master's and undergraduate students.As of 2025
- ProfessorTsuyoshi Hasegawa
VoicesStudent voices
Compiled from answers by students who were in the lab. Ratings and reviews reflect individual students' experiences, not the lab's official views.
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RelatedLabs similar to Hasegawa Lab
Aoki LabSchool of Advanced Science and Engineering, Department of Applied PhysicsQuantum optics
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Kita LabSchool of Advanced Science and Engineering, Department of Applied PhysicsPhotonic integrated devicesThe information on this page is compiled by the LabLog team from the lab's public information and interviews. For corrections or removal requests, please contact LabLog, not the lab.
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: “ESR-STM at QNS in Ewha - front view” Rickinasia / CC BY-SA 4.0 (cropped)
- Rock-paper-scissors with AI: “Schachfiguren -- (bw)” Dietmar Rabich / CC BY-SA 4.0 (cropped)
- In-sensor computing: “Venus Flytrap showing trigger hairs” Noah Elhardt / CC BY-SA 2.5 (cropped)
- Handwritten character recognition: “Snowflake macro (Unsplash)” Aaron Burden / CC0 (cropped)
- Physical reservoir using ion migration: “Scanning tunneling microscope (STM) 250 nm by 250 nm image of one-atom-thick silver islands grown on palladium (111) surface” Ponor / CC BY-SA 4.0 (cropped)
- Related lab (
青木研究室): “Fibres optique” Pastèque24 / CC BY-SA 4.0 (cropped) - Related lab (小澤研究室): “World First Hiperboloid structure named Shukhov Tower in Polibino” Arssenev / CC BY-SA 4.0 (cropped)
- Related lab (片岡研究室): “Fermi Gamma-ray Space Telescope spacecraft model” NASA / Public domain (cropped)
- Related lab (北研究室): “5C2A5953R - – Silicon Wafer 20200519” Rob Bulmahn / CC BY 2.0 (cropped)
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