Biography
I am currently a Master’s in Computer Science student at the University of Toronto and a member of the University of Toronto Robotics Institute. I am co-supervised by Prof. Florian Shkurti, as a member of the Robot Vision and Learning (RVL) Lab, and Prof. Igor Gilitschenski, as a member of the Toronto Intelligent Systems Lab (TISL).
Interests
- Autonomous Driving
- Deep Learning
- Robotics
- Computer Vision
Education
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MSc in Computer Science, expected 2023
University of Toronto
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BASc in Engineering Science, 2022
University of Toronto
Publications
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(2022).
Identify mangrove forests using satellite image features using Amazon SageMaker Studio and Amazon SageMaker Autopilot – Part 1.
Amazon Web Services (AWS) Machine Learning Blog.
(2022).
Identify mangrove forests using satellite image features using Amazon SageMaker Studio and Amazon SageMaker Autopilot – Part 2.
Amazon Web Services (AWS) Machine Learning Blog.
(2022).
Coordinated Multi-Agent Motion Planning via Imitation Learning.
ICRA Workshop on Fresh Perspectives on the Future of Autonomous Driving.
(2022).
Coordinated Multi-Agent Motion Planning via Imitation Learning.
University of Toronto.
(2020).
Myoelectric untethered robotic glove enhances hand function and performance on daily living tasks after stroke.
Journal of Rehabilitation and Assistive Technologies Engineering.
Experience
Data Science Intern
Amazon Web Services (AWS)
- Developed a deep learning‐based package volume forecasting pipeline using AWS Forecast to predict Amazon’s future customer demands for delivery station planning.
Professional Services Machine Learning Intern
Amazon Web Services (AWS)
- Designed and built an end‐to‐end, pixel‐level mangrove forest classification pipeline that could differentiate between mangrove and non‐mangrove regions in satellite images with >90% accuracy.
- Documented my contributions in a tutorial‐style blog post for the official AWS Blog.
- The project was completed successfully and a return offer was extended.
Summer Research Intern
- Worked with Prof. Florian Shkurti in the Robot Vision and Learning (RVL) Lab, self-funded through an Engineering Science Research Opportunities Program (ESROP) Award.
- Developed a novel CNN-based deep learning architecture for one-shot exemplar-based visual search from image and LiDAR data using PyTorch and OpenCV. Experimentally evaluated performance on the KITTI autonomous driving dataset, outperforming state-of-the-art methods.
Summer Research Intern
- Worked with Prof. Alex Mihailidis and Dr. Aaron Yurkewich in the Intelligent Assistive Technology and Systems Lab on the Hand Extension Robot Orthosis (HERO) Glove.
- Implemented a self-contained gesture recognition algorithm that leveraged support vector machines to learn and detect patients’ specified hand and arm movements from onboard accelerometer data to actuate the glove, using Python and C++.
- Designed and developed motion capture software using a PCB with a microcontroller and accelerometer, using C++.
- Assisted in developing a control algorithm using electromyography data which significantly improved hand function during clinical trials.