Ryan Yeung

Welcome! Here is where you can learn about all my projects and experiences

About me

Hello! I am a 3rd year biomedical engineering student at the University of British Columbia, specializing in biomedical signals and systems. I aspire to work in the robotics field, and would love to explore the role of robotics in healthcare technology.

Experiences

UBC Center for Brain Health: Raymond Lab Fiber Photometry Project May 2020 - August 2020

As an undergraduate research assistant, I helped design MATLAB scripts for behavioural and fiber photometry striatal neuron signal analysis of Huntington and wildtype mice models performing motor skill tasks. This helped identify meaningful differences and correlations between the wildtype and huntington mice models.

UBC Open Robotics Student Design Team January 2020 - present

At UBC Open Robotics, I am an electrical engineer helping to design the electrical portion of the arm component of the team’s flagship robotic project. We are currently working on designing the PCBs which will power and control the motors in the arm, as well as the firmware with which the software subteam can use to program the arm.

UBC BIOMOD Student Design Team December 2019 - present

As a member of UBC BIOMOD, I have been helping conduct background research and writing wetlab experimental procedures for the design of our novel DNA origami nano-hinge. Due to limitations from COVID-19 regulations, I have not yet had the opportunity to work directly in the lab.

Projects

Motion Feedback for Pregant and Postpartum Physiotherapy January 2020 - April 2020

In this project, I was challenged to design a medical device which could tackle the issue of physiotherapy exercise adherence. Our team decided to focus on physiotherapy for preganant and postpartum individuals, and proceeded to contact stakeholders to better understand the problem. Through a rigorous design process, we ended up designing a prototype for a marker-less pose identification device, along with a mobile application to track the user’s progress to promote adherence. In the prototyping phase, I contributed heavily towards the implementation of the marker-less pose identification software in JavaScript with PoseNet and ml5.js.