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Computing Systems Lab (Nakamura-Takase)
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A lab studying high-quality computing that bridges the physical world and the information world.
AboutAbout the lab
Connecting the physical and information worlds with high quality
The Nakamura-Takase Lab studies computing that connects the physical world and the information world at an advanced level.
Here, high quality refers to high performance, responsiveness, low power consumption, reliability, security, and similar attributes.
Because these attributes trade off against one another, each system needs to be optimized individually.
Targeting everything from edge devices such as sensors and robots to servers, the lab explores design methodologies that optimize systems through the coordination of circuit technology, architecture, and software.
Key terms
- Cyber-Physical Systems
- Systems that connect objects in the physical world to the internet, process the collected data in the information world, and act back on the physical world
- Edge Devices
- Devices placed in the field, such as sensors and robots, that collect data or take physical actions
- Acceleration
- Using circuits and mechanisms specialized for a target problem to perform computation faster and with less power
NewsLab news
A student who completed the master's program received the SICE Outstanding Student Award from the Society of Instrument and Control Engineers
A student who completed the doctoral program received the Dean's Award of the Graduate School
A master's student received the Best Poster Award (Silver) at SWEST27
A Project Assistant Professor received the Computer Science Area Encouragement Award from the Information Processing Society of Japan, and a doctoral student received the Young Researcher Encouragement Award from the ARC Research Group
A team of two students won second place at the FPGA AI Design Hackathon
ResearchResearch themes
The lab aims to establish high-quality computing and its design methodologies to enable advanced interaction between the physical world and the information world. Targeting entire systems from edge devices to servers, it investigates ways to optimize them through the coordinated integration of circuit technology, architecture, and software.
*Illustrative imageDistributed Machine Learning for Wide-Area IoT
The lab studies the theory and platform technologies that underpin distributed machine learning. Focusing on federated learning, it works on topics such as optimizing the placement of processing so that it can cope with changes in the resources and geographic information of IoT nodes.
*Illustrative imageCyber-Physical Systems
These are systems that connect objects in the physical world to the internet, process the vast amounts of data collected in the information world, and act back on the physical world. The lab studies design methodologies that realize the optimal computing for the characteristics and requirements of the processing.
*Illustrative imageResource-Transparent Computing Technologies
The lab studies platforms for wide-area distributed processing based on the functional programming paradigm. It works on a lightweight runtime environment for embedded devices built on ROS, as well as communication middleware with a high degree of autonomy and real-time performance.
*Illustrative imageHigh-Efficiency Acceleration Technologies
These technologies greatly increase computing power at low cost and low power consumption by specializing in the target problem domain. The lab focuses on coarse-grained reconfigurable architectures (CGRA), which optimize execution according to the characteristics of the processing.
MembersFaculty
The members of the Nakamura-Takase Lab consist of faculty, visiting researchers, administrative assistants, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorHiroshi NakamuraPublications ↗
- Associate ProfessorHideki TakasePublications ↗
- Assistant ProfessorTakeru Yazaki
- Project Assistant ProfessorHironori Ueno
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: “Pleiades two row” NASA Ames Research Center / Public domain (cropped)
- Distributed Machine Learning for Wide-Area IoT: “Artificial Neural Network with Chip” mikemacmarketing / photo on flickr / CC BY 2.0 (cropped)
- Cyber-Physical Systems: “Vista aérea de Avenida Cuauhtémoc 02” ProtoplasmaKid / CC BY-SA 4.0 (cropped)
- Resource-Transparent Computing Technologies: “Cyclope robot” Picture taken by Dake / CC BY-SA 3.0 (cropped)
- High-Efficiency Acceleration Technologies: “Mojo v3 FPGA Development Board ( )” SparkFun Electronics from Boulder, USA / CC BY 2.0 (cropped)
- Related lab (Numerical Informatics Lab): “Soliton hydro” Christophe.Finot et Kamal HAMMANI / CC BY-SA 2.5 (cropped)
- Related lab (Sound Media Informatics (Saruwatari-Saito Lab)): “Anechoic chamber-3” Togabi / CC BY-SA 4.0 (cropped)
- Related lab (Computational Informatics Lab): “SocialNetworkAnalysis” Martin Grandjean / CC BY-SA 4.0 (cropped)
- Related lab (Cryptography and Mathematical Informatics Lab): “Enigma-IMG 0487-black” Rama / CC BY-SA 2.0 fr (cropped)
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