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Nishio Lab
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A lab that combines wireless communications with computer vision and machine learning.
AboutAbout the lab
Integrating computing, communications, and sensing.
The Nishio Lab conducts interdisciplinary research centered on wireless communications and linked with computer vision and machine learning.
Under the banner of "integration of computing, communications, and sensing," the lab explores next-generation technologies for the IoT (Internet of Things), in which all kinds of things connect to the internet.
It develops methods to predict the strength of invisible radio waves from camera images, and mechanisms for devices on a network to learn cooperatively.
It is a relatively new lab, established in October 2020.
Key terms
- Computer vision
- Technology that lets computers read what appears in camera images or video, and the surrounding situation
- IoT
- A system in which everyday things such as smartphones, sensors, cars, and buildings are connected to the internet
- Federated learning
- An approach in which data is not gathered in one place; instead, each device trains on its own and the results are combined to build a single model
NewsLab news
Paper by a student accepted in IEEE Transactions on Mobile Computing
Held a lab tour for third-year undergraduates
Associate Professor Nishio received the Docomo Mobile Science Award
Paper by a doctoral student published in IEEE Transactions on Vehicular Technology
Paper by a doctoral student accepted in IEEE Internet of Things Journal
ResearchResearch themes
The lab conducts cross-disciplinary research centered on wireless communication systems. It rests on two pillars: research linking computer vision and wireless communications, and research on distributed, cooperative machine learning over wireless networks.
*Illustrative imagePredicting wireless communications from video
The lab develops technologies that use computer vision, such as analysis of camera images, to predict and control wireless communication conditions. This matters because millimeter-wave and terahertz signals weaken substantially when blocked by something as simple as a car or a pedestrian.
*Illustrative imageSeeing people and places with radio waves
The lab works on next-generation sensing technologies that estimate the number and activities of people in a room, and reconstruct video, from Wi-Fi and WiGig signals.
*Illustrative imageCommunication-efficient federated learning
The lab performs machine learning in a distributed way, making use of the data and computing power of devices on wireless networks, such as smartphones and sensors. It studies methods to reduce the amount of communication exchanged during training.
*Illustrative imageDistributed machine learning inference
The lab studies distributed machine learning inference methods that run efficiently even under constraints such as limited communication bandwidth and packet loss on the communication channel.
MembersFaculty
The members of the Nishio Lab consist of faculty and students in the doctoral, master's, and undergraduate programs.As of 2026
- Associate ProfessorTakayuki NishioPublications ↗
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: “Passive Millimeter Wave Camera (PMMWC) at TRW - GPN” Northrop Grumman Space Technology - Redondo Beach (formerly TRW, Inc)/TRW photographer / Public domain (cropped)
- Predicting wireless communications from video: “Base Transceiver Station in the Laji Mountain Pass (5G)” Michał Beim / CC BY 4.0 (cropped)
- Seeing people and places with radio waves: “Wi-fi router” Solijon Solayev / CC BY-SA 4.0 (cropped)
- Communication-efficient federated learning: “CSIRO ScienceImage 3876 A remote sensing node part of CSIROs Fleck wireless sensor network technology” Stephan Brosnan, CSIRO / CC BY 3.0 (cropped)
- Distributed machine learning inference: “Circumference C )” Gareth Halfacree from Bradford, UK / CC BY-SA 2.0 (cropped)
- Related lab (山岡・北口研究室): “Network cables and switch” ProjectManhattan / CC BY-SA 3.0 (cropped)
- Related lab (宮田研究室): “Minato City, Tokyo, Japan (Night)” David Kernan / CC BY 4.0 (cropped)
- Related lab (スラヴァキス研究室): “The manifold paths of biology ( )” UCL Mathematical & Physical Sciences / CC BY 2.0 (cropped)
- Related lab (篠﨑研究室): “Human voice spectrogram” Dvortygirl, Mysid / CC BY-SA 3.0 (cropped)
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