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Nodoka Shibasaki

Electrical and Computer Engineering Student
Northeastern University
shibasaki.n (at) northeastern.edu


About Me

I am a fourth-year Electrical and Computer Engineering student at Northeastern University. Under the supervision of Professor Taskin Padir, I am currently researching manipulation and autonomy.

Until December, I am researching robot manipulation for warehouse applications at the Innovation Lab at Amazon Robotics. Additionally, I am contributing to the open source SONiC Platform Driver Development Kit under the close guidance of mentors at the Linux Foundation.

In the past, I gained valuable industry research experience as a Research Intern at OMRON SINIC X in Tokyo where I researched contact-rich manipulation for soft robotics. During my undergraduate studies, I also had the opportunity to develop autonomous multi-modal locomotion robots under Professor Alireza Ramezani, and uncertainty-aware exoskeletons under Professor Max Shepherd.

Hobbies:
😋 Trying new restaurants
👩‍💻 Browsing for tools
🏀 Basketball, Running
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Timeline

* Highlighted are ongoing positions

2025
Robotics Research Intern @ OMRON SINIC X
2026
Research Assistant @ Northeastern, RIVeR Lab
2026
Hardware Engineer Intern @ Amazon Robotics
2026
Software Engineer Intern @ The Linux Foundation

Selected Projects

* Highlighted are ongoing projects intended for future publication.

HASHI

Image from A. Allison et al.

Jan 2026 - Present | RIVeR Lab
Investigates imitation learning for contact-rich tasks using an xArm robot with a custom chopsticks gripper. The project explores mapping human teleoperation data to dexterous manipulation policies.
Articulate Tool Data Collection
Jan 2026 - Present | RIVeR Lab
Investigates how robots can learn contact-rich tasks from sensor data by observing object interactions. The project explores turning these observations into representations that improve dexterous manipulation.
Jan 2026 - Present | RIVeR Lab
LUCI-enabled autonomous wheelchair uses RGB-D camera and robotic arm for urban navigation and manipulation.
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.
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 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. As I began working on assistive robotics in college, however, I found myself more captivated by solving the challenge of creating adaptive systems that work at and alongside human capability in open, real-world environments. I am especially interested in tackling this through robotic manipulation.

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