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Constructive Electronics Lab
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A lab that uses neural circuits as a clue to build next-generation information processing.
AboutAbout the lab
Putting neural circuit technology to work in next-generation circuits.
The Constructive Electronics Lab aims to extract useful technologies from biological neural circuits and apply them to next-generation information-processing hardware.
The Yajima Group covers materials, devices, and circuits, while the Kawakami Group covers circuits, architecture, and computational principles, and the two groups carry out research in collaboration.
The Yajima Group studies materials that show phase transitions and devices that use protons, and the Kawakami Group studies computers built from new optical and superconducting devices.
On the lab's website, the lab is also introduced under the name "Yajima-Kawakami Lab."
Key terms
- Phase transition
- A phenomenon in which a material greatly changes its properties (physical property values) across a certain boundary.
- Neuromorphic
- An approach to building devices and circuits that uses biological neural circuits as a guide.
- Spike signal
- A signal that biological neural circuits use to exchange information.
- Proton
- The smallest ion. It corresponds to the nucleus of a hydrogen atom and can move around even inside solids.
NewsLab news
A master's student received a Kyushu University Student Award
A master's student received an Outstanding Student Award from the Graduate School of Information Science and Electrical Engineering
A master's student received the Best Student Paper Award at OECC/PSC 2025
ResearchResearch themes
The more advanced information technology becomes, the more electric power and communication bandwidth are consumed. Using biological neural circuits as a clue, this lab studies next-generation information-processing hardware built with circuit technology and materials technology.
*Illustrative imageEnergy-efficient, high-speed sensors using phase transition materials
The lab uses the property that a material's physical properties change greatly at a phase transition to develop sensors that can be embedded directly in digital circuits. Because the material itself performs the "measurement," the lab expects ultra-low-power, high-speed sensing to become possible.
*Illustrative imageNeuromorphic devices using electrons and protons
In joint research with companies, the lab focuses on the fact that protons, the smallest ions, can move freely through solids, and controls electrons and protons simultaneously in solid-state devices. It aims to realize new functions that are fundamentally different from conventional electronics.
*Illustrative imageUltra-low-power processing driven by spike signals
In joint research with companies, the lab focuses on the fact that biological neural circuits operate coupled with the real world in real time through spike signals. It aims to realize efficient electronic control without waste that meets the strict low-power requirements of IoT devices.
*Illustrative imageEnergy-efficient learning circuits for reservoir computing
The lab builds ultra-low-power learning circuits based on reservoir computing algorithms, aiming to construct hardware that uses learning functions to perform anomaly detection and prediction flexibly.
MembersFaculty
The members of the Constructive Electronics Lab are faculty members, staff, PhD, master's, and undergraduate students, and research students.As of 2026
- Associate ProfessorTakeaki Yajima
- Associate ProfessorSatoshi Kawakami
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: “SIP integrated circuits package” Mister rf / CC BY-SA 4.0 (cropped)
- Energy-efficient, high-speed sensors using phase transition materials: “CMOS image sensor chip-scale package oblique” Phiarc / CC BY-SA 4.0 (cropped)
- Neuromorphic devices using electrons and protons: “Artificially altered material could accelerate neuromorphic device development ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
- Ultra-low-power processing driven by spike signals: “DARPA SyNAPSE 16 Chip Board” DARPA SyNAPSE / Public domain (cropped)
- Energy-efficient learning circuits for reservoir computing: “Gyrator-Capacitor Model Example Transformer with Gap and Leakage Flux Schematic” Constant314 / CC0 (cropped)
- Related lab (High Performance Computing Lab): “IBM Blue Gene P supercomputer” Argonne National Laboratory's Flickr page / CC BY-SA 2.0 (cropped)
- Related lab (Functional Integrated Systems Lab): “SJ3159 die” Mister rf / CC BY-SA 4.0 (cropped)
- Related lab (Wireless Communications Lab): “Wireless antenna on boat 1914-colorized” 作者不詳 / Public domain (cropped)
- Related lab (Nanophotonic Information Applications Lab): “Quantum dots 3” Marc Vidal / CC BY-SA 4.0 (cropped)
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