Papers

34

Total Citations

795

H-Index

15

About

Ryohei Kanzaki is a pioneering researcher at the intersection of neuroscience, robotics, and bioengineering, whose work has fundamentally advanced our understanding of insect olfactory behavior and its technological applications. His research centers on decoding the neural mechanisms underlying odor-source searching in insects — particularly silkmoths — and translating these biological principles into functional robotic systems. Kanzaki's most celebrated contributions include his landmark 1999 study (133 citations) in which he equipped a mobile robot with live moth antennae to replicate pheromone-guided navigation, elegantly demonstrating how instinct-driven behavior can be synthetically reconstructed. This was complemented by his development of highly sensitive cell-based odorant sensors using insect olfactory receptors expressed in Xenopus oocytes, achieving detection at parts-per-billion concentrations (129 citations). His research on insect-machine hybrid systems — including brain-machine interfaces and the innovative 3-DOF servosphere locomotion platform — has opened new frontiers in neuroprosthetics and adaptive robotics. Beyond hardware, Kanzaki's behavioral algorithms inspired by moth plume-tracking have influenced autonomous chemical detection systems in turbulent environments. Spanning nearly three decades of influential publications, his interdisciplinary work bridges fundamental neuroscience with real-world engineering applications, making him a defining figure in biohybrid robotics research.

Research Focus

Key Achievements

15
H-Index
34
Papers
795
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
Synthesis of the pheromone-oriented behaviour of silkworm moths by a mobile robot with moth antennae as pheromone sensors1This paper was presented at the Fifth World Congress on Biosensors, Berlin, Germany, 3–5 June 1998.1
133 citations · 1999
📈 Most Prolific Year: 2010 (4 Papers)
🤝 Key Collaborators: 42
🏛 Institutions: University of Tsukuba, The University of Tokyo, Tokyo University of Science

Top Papers

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    Insect-machine hybrid robot
    39 citations · 2020
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Key Collaborators

Contact & Links

Available for collaboration
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