Yue (Kathy) Zhuang

Hey there, and a warm welcome to my personal website! As a student researcher captivated by innovative technologies and machine learning, I am thrilled to share my journey with you.

I recently completed my undergraduate studies at the University of Toronto in Engineering Science, majoring in machine learning and minoring in robotics. It was during this time that I discovered my passion for machine learning and its applications in computer vision, particularly in the realms of human-computer interaction and robotics perception.

Starting August 2023, I'll be pursuing my master's degree in Electrical Engineering and Computer Science at the University of California, Berkeley, where I'll be immersing myself in the Visual Computing and Computer Graphics track.

On this website, you'll uncover my passion for machine learning, computer vision, and robotics, along with a glimpse into my personal hobbies, such as watercoloring and graphic design.

Resume Email LinkedIn

Education

University of California, Berkeley | Aug 2023 – May 2024

M.Eng. in Electrical Engineering and Computer Science
Visual Computing and Computer Graphics track
UC Berkeley College of Engineering Opportunity Grant (2023)

University of Toronto, St. George Campus | Aug 2018 – Jun 2023

B.A.Sc. in Engineering Science
Machine Intelligence major, Robotics minor
Engineering Science Research Opportunity Fellow(2020), Dean’s List (2018-2023), Dean’s Merit Award (2018)

Work Experience

Amazon.com, Inc. | May 2023 – Jul 2023 | Vancouver, BC, Canada

Software Development Engineer Intern | Consumer Payments

● Enhanced user experience and resource infrastructure on a payment partner outage alert platform, ensuring swift notifications for onboarded clients and minimizing adverse effects
● Proficiently orchestrated and executed enhancements using TypeScript, JavaScript, Kotlin, HTML, and CSS. Deployed the application to production, resulting in enhanced operational efficiency for over 30 clients utilizing the platform.

Amazon.com, Inc. | May 2022 – Jul 2022 | Seattle, WA, USA

Software Development Engineer Intern | Consumer Payments

● Created a RESTful API in Java and Kotlin allowing CRU operations to mock the behavior of third-party partners
● Implemented API integrated with various AWS technologies such as ECS and S3 Cloud Storage to allow for the current workflow to be accurately modelled and efficiently tested

Huawei Technologies Canada Co., Ltd | May 2021 – Apr 2022 | Markham, ON, Canada

Machine Learning Engineer Intern | Human-Machine Interaction Lab

● Developed eye region detection and object tracking modules with machine learning models and integrated them into in-car Infrared-based eye gaze tracking system
● Trained machine learning models that took RGB facial images as input and provided real-time video-based eye gaze tracking on laptops and smartphones

Research Experience

Robot Vision and Learning Lab, University of Toronto | Jun 2022 – Present | Toronto, ON, Canada

Research Assistant, Supervised by Profs. Florian Shkurti & Animesh Garg

● Developing a pipeline for injecting realistic sensor noise into depth images in a synthetic RGB-D transparent object dataset using generative models such as CycleGAN and Diffusion
● The synthetic dataset is used in the training of a transparent object detection network in a perception system used to manipulate robot arm in a chemistry lab setting

BMO Lab in Creative Research in Arts, Performance, Emerging Tech & AI | Feb 2021 – Feb 2023 | Toronto, ON, Canada

Research Assistant, Supervised by Prof. David Rokeby

● Used Contrastive Language-Image Pre-Training (CLIP) to guide search through latent space of VQGAN to generate panoramic voice scenes in real time.
● Implemented Open Sound Control and Pytorch Distributions to allow users to control the generation of animation using spoken words within a live performance featuring artists from the Toronto region.
link to the performance recording

3D Perception Team, aUToronto Self-Driving Team | Mar 2021 – Mar 2022 | Toronto, ON, Canada

Research Engineer

● Implemented LiDAR-based object detection and ground plane removal algorithms in C++ and ROS2.
● Deployed and tested point cloud clustering pipeline in C++.
● Won 1st place overall in the 2022 SAE Autodrive Challenge II Year 1 competition sponsored by General Motors.
link to the project website

Intelligent Sensory Microsystems Lab, University of Toronto | May 2020 – Sep 2020 | Toronto, ON, Canada

Computer Vision Research Assistant, Supervised by Prof. Roman Genov

● Integrated auto-tuning structured light machine learning model on novel Coded-Exposure-Pixel camera to realize quick 3D image construction
● Generated disparity and albedo maps from structured light using Python, Bash, and Matlab
● Developed demos for Coded-Exposure-Pixel cameras on 3D reconstruction and multispectral imaging

Information Systems Group, University of California, Irvine | Jun 2019 – Aug 2019 | Irvine, CA, USA

Research Assistant, Supervised by Prof. Chen Li

● Performed social media & environmental data visualization/analysis in machine learning pipeline to predict wildfires
● Implemented web scraper of real-time tweets in Python; integrated Twitter API to retrieve 1000+ tweet data daily
● Designed/developed Leaflet map layers to visualize fire event polygons with Angular2+ and TypeScript

Other Noteworthy Projects

Machine Intelligence CAPSTONE Design with Clarifai Inc.

Attained Highest Grade in Class for CAPSTONE Project

Worked with Clarifai Inc. to develop a multimodal model trained with the Meta Hateful Meme Challenge dataset capable of performing content moderation
Focused on augmenting the hateful meme dataset using text removal, object classification, CLIP, and Stable Diffusion.

Details

The Autonomous Electric Car Charging Solution

Collaboratively worked with 2 team members to develop an autonomous electric car charging machine using Arduino programming and electrical & mechanical designs. Applied computer vision, robotic control systems, 3D printing and CAD

Github

A Household Item Recognition System for Visually Impaired Individuals

Developed an object localization and classification system that can easily recognize household items to help visually challenged people.
● Applied Detectron2, a Mask RCNN model to realize object localization
● Built a Capsule-CNN model to achieve object classification using Pytorch.
● Adopted various image data processing techniques including segmentation and thresholding on the CORe50 (Continual Object Recognition) dataset.

Github

One-Way-Only Novel Package Storage System

2020 MakeUofT Hackathon MLH Winner Project

Created a system with user identification function and unique automated joint design to restrict delivery direction and bring packages into home securely.
● Delivered an interactive prototype including a 3D-printed model with CAD and integrated circuit with Arduino.
● Accomplished highest performance in functionality and creativity.

Devpost

Blue-Block Blocking System for Wandering Dementia Patients in Long-Term Care Facilities

Ranked Among Top 8 out of 60 Class Request for Proposals (RFP)

Proposed and created a blocking and securing system for wandering dementia patients living in long-term care facilities. The system created enables patients wearing blue-tooth wristbands to access their room only rather than entering other patients’ rooms.
● Collaboratively worked with 3 team members to build a working electricity-driven prototype using Arduino, circuits, Bluetooth sensors and stepper motors.
● Stakeholder invitation to present the team result at the Kitchener Innovation Summit in front of 200+ personal service workers.

Github

Creative Escapes: Painting and Graphic Design in My Free Time

Welcome to my realm of creative escapes! When I'm not busy with school or work, I always immerse myself in the realms of painting and graphic design. This is where I unleash my imagination and allow my artistic endeavors to take flight. Feel free to browse through this section to catch a glimpse of what I love to do during my free time.