About Me

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 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.

Publications

Journal & Conference Papers
  • Adaptive Chirplet Transform-Based Neural Network for Seizure State Detection IEEE International Conference on AI in Information and Communication (ICAIIC), 2026.
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  • Portable EEG-Based Data Acquisition and Multi-Sensor Integration Using the Muse S Headband IEEE International Conference on Control, Automation and Diagnosis (ICCAD), 2025.
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  • MoBorg: Mobility as Cyborg Prosthesis for “Being a Ball” IEEE Games, Entertainment and Media (GEM), 2025.
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  • Adaptive Chirplet Transform-Based Sleep State Detection IEEE International Conference on Consumer Electronics (ICCE), 2025.
    Best Poster Paper Award View Publication
  • Smart Rollator Walker for Enhanced Mobility IEEE International Conference on Consumer Electronics (ICCE), 2025.
    Best Session Paper View Publication
  • XR Waterball for Spinal Rehabilitation Second International Workshop on Human-centered Sensing, Networking, and Multi-Device Systems (HumanSys), 2024.
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Edited Volumes / Proceedings
  • Proceedings of the 27th Annual Mersivity / Water-HCI Symposium (December Edition) Proceedings Chair
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  • Proceedings of the 27th Annual Mersivity / Water-HCI Symposium (August 2025) Publication Chair
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Accepted / In Press
  • GPU-Accelerated Chirplet Transform: Scalable Runtime Profiling and Analysis IEEE International Conference on Sensing Technologies (ICST), 2025.
    Accepted

Projects

Drone icon

Drone Development

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.

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GPU-Accelerated Chirplet Transform

Developing a GPU-accelerated Chirplet Transform optimized for real-time signal processing and analysis.

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Quantifying Biomechanical Movements

System to measure ankle and spine movements in 3D using IMU sensors, stereo vision, and human segmentation with YOLO.

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Awards

  • Best Poster Paper Award IEEE International Conference on Consumer Electronics (ICCE) 2025
  • Best Session Paper IEEE International Conference on Consumer Electronics (ICCE) 2025

Contact

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