Ryan Zeyuan Chen

I am a second year Mechanical Engineering MASc student at the University of Toronto. I am advised by Andrew Goldenberg and a member of the Robotics and Automation Laboratory.

I previously served as a Research Intern at the Surgical Imaging and Mechatronics Laboratory under the supervision of Jayender Jagadeesan at Brigham and Women's Hospital and Harvard Medical School. I also completed my Undergraduate Thesis at the Continuum Robotics Laboratory, under the guidance of Jessica Burgner-Kahrs at the University of Toronto Robotics Institute. In addition, I was formerly a Research Assistant at the Microfluidics and BioMEMS Laboratory, where I worked under the mentorship of Xinyu Liu.

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I am interested in the sensing, modeling, and control of soft and medical robots utilizing machine learning. Compared to the rigid mechanical structure of conventional robots, the inherent compliance and flexibility of soft robots enable them to travel in confined spaces and manipulate objects in complex environments. In medical applications, such robots provide clinicians with the ability to administer less invasive treatments at a reduced cost and higher efficiency.

My current research focuses on the development of a data-efficient and generalizable framework for learning the kinematics of robots, with an application to concentric tube continuum robots.

A novel hydrogel-based ionic skin with demonstrated applications in wearable sensing, human-machine interaction and soft robotics.

The first public dataset of a three-tube concentric tube continuum robot, accompanied by benchmark results for learning the forward kinematics using a feedforward neural network.

I have worked on a wide range of interesting and challenging projects within the domains of robotics and machine learning.
These experiences broadened my perspective and equipped me with a comprehensive understanding of the robotics field.

The design and implementation of a tendon-driven continuum robot for efficient detection and removal of cancerous polyps in the large colon.

The design and implementation of an intelligent dog walking robot with real-time visual dog tracking, dog following, and dog waste disposal capabilities.

The design and implementation of an intelligent robotic shopping cart with customer following, shopping guide, and auto-checkout features.

The recognition of wine grape variety through wine taste descriptions utilizing the long short-term memory (LSTM) neural network model.

The design of a gesture controlled claw machine facilitated by a wearable device, as an alternative to traditional joystick control.

The design and construction of an autonomous robot for the PacBot competition hosted by the Harvard Undergraduate Robotics Club, mimicking the traditional Pac-Man game in a physical arena. Organized and led weekly meetings with team members, focusing on the design and implementation of circuits and sensors for the robot as the electrical team lead.

The design of a control system, based on Bayesian-localization techniques, for the TurtleBot 3 Waffle Pi robot to deliver mail to arbitrarily chosen stations on a closed-loop route.

The design and fabrication of a scaled-down, proof-of-concept prototype of a mobile platform that can travel along a designated lane and deploy traffic cones.