Koki Shinjo
Papers
8
Total Citations
47
H-Index
5
About
Koki Shinjo is a robotics researcher pushing the boundaries of musculoskeletal humanoids—robots that closely mimic the human body's redundant sensors and flexible structure. His most impactful work centers on autonomous driving with these humanoids, demonstrating how their complex, human-like bodies can master tasks requiring intricate environmental contact, such as pedal control. In a 2020 paper (14 citations), he summarized the hardware and learning-based software enabling this breakthrough, while a 2019 study (9 citations) tackled the challenge of self-modeling for flexible bodies, introducing an online method to acquire the nonlinear muscle-joint relationship. Beyond driving, Shinjo has innovated in anomaly detection for daily-life robots, using pre-trained vision-language models to detect semantic scene differences (2023, 8 citations). His recent work includes a system for generating automatic diaries of joint human-robot experiences (2024, 6 citations) and a stochastic predictive network for environmentally adaptive control (2021, 5 citations). Notably, his 2025 research on liquid metal sloshing for self-healing tendons in legged robots—capable of recovering over 1kN tensile strength after fracture—represents a leap in high-load damage management. With a portfolio spanning autonomous driving, human-robot interaction, and resilient hardware, Shinjo is a rising figure in embodied AI and bio-inspired robotics.
Research Focus
Key Achievements
Top Papers
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