Illustrated portrait
MASc researcher
Aaron Yu
Aaron develops hardware-efficient spiking neural systems for event-based gesture processing and line detection.
- Program
- MASc
- Supervision
- Leonard MacEachern
- Co-supervision
- Arash Ahmadi, Electronics
- Last updated
- 22 July 2026
Place in MOSAIC
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Research overview
Aaron researches spiking neural networks implemented in FPGAs under the joint supervision of Leonard MacEachern and Arash Ahmadi in Electronics. His work connects event-based sensing, neuromorphic computation, algorithm design, and efficient hardware architecture.
The research asks how sparse, event-driven computation can be mapped into fixed and reconfigurable hardware while preserving useful temporal and spatial structure.
Published work
- Low-Cost Spiking Networks on FPGA for Event-Based Gesture Detection, with Arash Ahmadi and Leonard MacEachern, ISSCS 2025.
- A Spiking Neural Network Based Hough Transform Implementation for FPGAs, with Leonard MacEachern and Arash Ahmadi, IEEE Transactions on Emerging Topics in Computational Intelligence, 2026.
Technical focus
- Spiking and neuromorphic neural networks
- Event-based gesture and vision processing
- Hough-transform line detection
- FPGA architecture and implementation
- Resource-aware and low-cost hardware design
- Real-time sensory computation
Current direction
Aaron’s profile will grow with thesis milestones, architecture figures, verified implementation results, publications, presentations, code, and project artifacts.