CV
Contact: yamanokuchi.tomoya[at]naist.ac.jp
Current Position
Present
Specially Appointed Assistant Professor
Robot Learning Lab, Nara Institute of Science and Technology (NAIST)
Robot Learning Lab, Nara Institute of Science and Technology (NAIST)
Education
2021.4 – 2024.3
Doctoral Course, Division of Information Science, NAIST, Japan
Thesis: Disentangled Dynamics Learning through Randomized-to-Canonical Visual Translation for Sim-to-Real Robotic Manipulation [Link]
Thesis: Disentangled Dynamics Learning through Randomized-to-Canonical Visual Translation for Sim-to-Real Robotic Manipulation [Link]
2019.4 – 2021.3
Master’s Course, Division of Information Science, NAIST, Japan
2017.4 – 2019.3
Advanced Engineering Course, Electronic Engineering Program, National Institute of Technology (KOSEN), Niihama College
2012.4 – 2017.3
Department of Electronics and Control Engineering, National Institute of Technology (KOSEN), Niihama College
Research Stays Abroad
2024.9 – 2024.12
Visiting Scholar, Intelligent Autonomous Systems Laboratory (IAS-Lab), University of Padua, Italy
18 September – 13 December 2024
18 September – 13 December 2024
2023.10 – 2023.11
Awards
2025
Best Paper Award Finalist, IAS-19
2022
IEEE Robotics and Automation Society Japan Joint Chapter Young Award [IEEE RAS JJC] [NAIST]
2022
博士キャリアメッセKYOTO 島津製作所賞 [NAIST]
Scholarships & Grants
2026.4 – 2029.3
Grant-in-Aid for Early-Career Scientists, Japan Society for the Promotion of Science (JSPS), Principal Investigator [KAKEN]
Project: “Causal Imitation Learning for Task Automation from a Small Number of Demonstrations” (Grant No. 26K21353, total funding: JPY 2.73 million)
Project: “Causal Imitation Learning for Task Automation from a Small Number of Demonstrations” (Grant No. 26K21353, total funding: JPY 2.73 million)
2023
Japan Society for the Promotion of Science (JSPS), Research Fellowship for Young Scientists (DC2)
2023
Japan Student Services Organization (JASSO), Scholarship (half-amount return exemption)
2021
Japan Student Services Organization (JASSO), Scholarship (half-amount return exemption)
Skills
- Deep learning libraries: PyTorch, TensorFlow 1
- Programming languages: Python, MATLAB
- Image processing: OpenCV
- Robot system integration: ROS 1, ROS 2
- Robot simulation: MuJoCo
- Software design: Domain-Driven Design
Media
2022.10.28