Gawtham Senthilvelan
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Engineer in Toronto working at the intersection of communications and digital design. Focused on FPGA acceleration, signal processing, and applied AI.
The frequency.
I translate complex signal workflows into elegant systems, balancing rigorous engineering with human-centered digital design.
Focus
FPGA acceleration, RF systems, and applied AI. I obsess over signal clarity, latency, and the quiet details that make systems feel alive.
Approach
Crafting scalable architectures and interfaces that feel calm under pressure, so teams can move fast without losing the signal.
Selected projects.
Deep learning computer vision system for chess piece recognition achieving 99.5% accuracy using ResNet-inspired CNN with OpenCV preprocessing.
Built an RF front-end that filters, downconverts, and amplifies 8–16 MHz HF signals with quadrature mixer producing phase-accurate I/Q signals for SDR integration.
Real-time robotic arm controller using C on NIOS V soft processor with AXI memory-mapped I/O, custom PID loop, VGA dashboard, and I²C bridge for PWM servo control.
FFT-based spectral analysis on FPGA using SystemVerilog for real-time audio DSP with MATLAB filter ports to ARM Cortex-M for embedded benchmarking.
Experience.
ASIC Engineer Intern
Qualcomm · Markham, ON
Incoming May 2026.
Machine Learning Researcher
RBC Borealis · Toronto, ON
Machine learning optimization of atmospheric water harvesting systems.
Software Developer
Acceleration Consortium · Toronto, ON
Bayesian optimization for laboratory automation.
Researcher
Advanced Membranes Lab · Toronto, ON
Advanced synthesis of membranes for high-pressure reverse osmosis. Supervisor: Dr. Jay Werber.
Technical writing.
A first-principles walkthrough of OFDM, from delay spread and coherence bandwidth to orthogonality and practical FFT/IFFT-based implementation.
An intuitive build-up from signals and Fourier series to the DFT and twiddle-factor symmetry, showing why FFT reduces complexity from O(N^2) to O(N log N).