Dr. Lu’s new project and Dr. Ruichen Li’s new project have been accepted for Grant-in-Aid for JSPS Fellows and for Research Activity Start-up

The following projects, for which Dr. Lu and Dr. Ruichen Li serve as a Co-Investigator and the Principal Investigator, have been accepted for Grant-in-Aid for JSPS Fellows and for Research Activity Start-up, respectively. Grant-in-Aid for JSPS Fellows“Predictive coding in children’s context-based learning of homophones” [KAKEN] Co-Investigator: Youtao Lu Period: 2024.07-2027.03 Grant-in-Aid for Research Activity Start-up“Multi-system modeling method revealing interaction among […]

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Interdisciplinary Workshops on Interoceptive Awareness will be organized on May 22 & 27 2024

We are going to organize Interdisciplinary Workshops on Interoceptive Awareness: Bridging Research Across Cultures in IRCN, the University of Tokyo, May 22 & 27, 2024. The aim of the workshops to share and discuss interdisciplinary research on interoceptive awareness. You all are cordially invited. Interdisciplinary Workshops on Interoceptive Awareness: Bridging Research Across Cultures, The University of Tokyo, May 22 & […]

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We start accepting graduate students through the Graduate School of Medicine, the University of Tokyo

Nagai-lab has became a collaborating lab at Department of Neuroscience, Graduate School of Medicine, the University of Tokyo. We start accepting graduate students to supervise toward their Master/Ph.D degrees. Please check the following pages for details: Department of Neuroscience, Graduate School of Medicine, The University of Tokyo Call for Postdoctoral Fellows, Graduate Students, and Internship Students

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Paper co-authored by Mr. Aktas, Prof. Ugur, and Project Prof. Nagai has been accepted in IEEE Robotics and Automation Letters

A paper co-authored by Mr. Aktas, an IRCN Internship Student, Prof. Ugur, an IRCN Guest Researcher, and Project Prof. Nagai has been accepted in IEEE Robotics and Automation Letters. The paper presents a neural network for correspondence learning between morphologically different robots. Hakan Aktas, Yukie Nagai, Minoru Asada, Erhan Oztop, and Emre Ugur, “Correspondence Learning Between Morphologically Different Robots via […]

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