Embedded & Biomedical Engineering — Neuroengineering, Wearables, Signal Processing
I am a Master’s researcher in Electrical and Computer Engineering at the University of Toronto, working under Dr. Steve Mann. My research focuses on neuroengineering systems that integrate signal processing, embedded computing, and hardware acceleration, with applications in EEG analysis, wearable sensing, and rehabilitation technologies.
My current work includes GPU-accelerated adaptive time–frequency methods, embedded EEG data acquisition systems, and assistive robotics.
Designing and building a custom drone, with a 3D-printed optimized frame and an embedded C++ flight controller featuring real-time sensor fusion and motor control. Work is ongoing to refine sensor integration and flight stability, and a public repository is available to track progress.
Thesis project focused on developing a GPU-accelerated Chirplet Transform optimized for real-time signal processing and analysis. The public repository contains preliminary work based on published and accepted results, while ongoing improvements and optimizations remain part of the current research. View repository.
Developed a system to measure ankle and spine movements in 3D using IMU sensors, stereo vision, and human segmentation with YOLO. Real-time data visualization was implemented in Processing, with depth mapping and PCA applied for analyzing movement patterns. The project was completed in 2024 as part of the Mersivity 2024 Symposium, and a public repository is available for reference.