Nodoka Shibasaki
About Me
I am a third-year Electrical and Computer Engineering student at Northeastern University with a strong intent to pursue robotics. I am currently a research assistant in the RIVeR Lab under the supervision of Professor Taskin Padir.
My interest in robotics has solidified thanks to many guidances. I had the opportunity to develop autonomous multi-modal locomotion robots at the Silicon Synapses Lab under Professor Ramezani Alireza, and uncertainty-aware exoskeletons at the Shepherd’s Lab under Professor Max Shepherd.
I also gained valuable industry research experience as a full-time intern for six months at OMRON SINIC X in Tokyo.
| 2004 | Born in Tokyo, Japan |
|---|---|
| 2015 | Moved to Cupertino, CA |
| 2020–23 | Biomechanics & ML Intern @ Stanford |
| 2020–23 | Founder & Executive Dir @ JTutor |
| 2024 | Founder & President of Asian Student Association @ Northeastern Sattelite Campus |
| 2024 | Software Engineering Intern @ London South Bank University |
| 2024–25 | Robotics Intern @ Shepherd Lab |
| 2025 | Control & Simulations Intern @ Silicon Synapses |
| 2025 | Service Director @ Phi Sigma Rho |
| 2025 | Operations @ Boston Hack BeanPot |
| 2025 | Robotics Intern @ OMRON SINIC X |
| 2026 | Robotics Researcher @ RIVeR Lab |
Projects
Autonomous Wheelchair Navigation and Manipulation
Jan 2026 - Present | RIVeR Lab
LUCI-enabled autonomous wheelchair uses RGB-D camera and robotic arm for indoor navigation and manipulation in Isaac Sim. Features include door-opening capabilities and autonomous task execution.
Active vs. Passive Control with FT feedback
Jul 2025 – Dec 2025 | OMRON SINIC X
Comparative study of passive compliance (soft wrist, position control) versus active compliance (Forward Dynamics Compliance Controller, rigid wrist) on a UR5e using SAC reinforcement learning with force-torque feedback only.
Tactile Memory with Soft Robots
Jul 2025 – Dec 2025 | OMRON SINIC X
TaMeSo-bot uses transformer-based learning to process tactile, force-torque, and proprioceptive signals for retrieval-based manipulation. Achieved 88.5% and 62% success rates under seen and unseen peg-in-hole conditions (varying shapes, sizes, textures, orientations).
Multi-Modal Locomotion Robot
Jan 2025 – July 2025 | Silicon Synapses Lab
M4 platform uses a reproducible sim-to-real pipeline built with ROS 2, ArduPilot, and Docker for multi-modal locomotion. Reduced deployment time by 40% and improved energy efficiency by 18% across aerial and ground modes.
Ankle Exoskeleton
Sep 2024 – Jun 2025 | Shepherd Lab
Modular ankle exoskeleton uses flexible CAD system and integrated sensor pipelines for rapid prototyping and biomechanical testing. Accelerated hardware-control iteration cycles, enabling foundation for ML-driven gait assistance.
Hip Exoskeleton
Jun 2024 – Feb 2025 | Shepherd Lab
Hip exoskeleton uses optimized power system with RL-based control policy for adaptive gait assistance under variable human movement. Reduced metabolic cost by 38.5% and improved stability, enabling extended human-in-the-loop trials.
My early work in athletic training and at Stanford Sports Medicine Lab initially drew me toward biomechanics and pre-med. But as I began working on assistive robotics in college, I found myself more captivated by solving the challenge of creating adaptive systems that work with human capabilities in a open world setting. I am especially interested in tackling this through reinforcement learning, and multi-modal sensory integration.
Hobby
composition of activities I spend too much time on
- Trying new restaurants and cafes: Tokyo Food Review
- Optimizing workflow and settings on MacOS
- Exercising: Basketball, Running, Weightlifting
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