I specialize in embedded systems and firmware development, with a focus on AI and machine learning integration on edge and resource-constrained devices.

My work spans bare-metal and embedded Linux systems, low-level firmware, and end-to-end embedded AI pipelines—from real-time sensor acquisition to optimized ML inference running close to the hardware.

I am particularly interested in building predictable, efficient systems that combine traditional embedded control logic with ML-driven perception and decision-making for IoT, robotics, and intelligent devices.

• ARM Cortex-M/A/R Architectures
• Bare-metal and RTOS-based development
• GPIO, SPI, I²C, UART, timers, interrupts
• Memory-mapped I/O and register-level programming
• Boot processes and system initialization
• Multithreading, concurrency, synchronization
• Embedded Linux internals
• Hardware–software integration

• OpenCV-based real-time vision pipelines
• Lightweight ML models for embedded deployment
• Model optimization techniques (quantization, reduced precision)
• Edge inference on Raspberry Pi–class hardware
• Integration of ML inference with firmware control and system logic
• Core ML algorithms such as linear regression and gradient descent

• Designed a Raspberry Pi–based embedded system for real-time sign language translation
• Integrated sensors and peripherals via SPI under embedded Linux
• Implemented low-latency gesture recognition using OpenCV and ML models

• Built a minimal OS kernel in C++ and Assembly
• Implemented bootstrapping, memory management, interrupts, and basic I/O
• Validated system behavior in a virtualized environment

• Developed a concurrent server emphasizing correctness and thread safety
• Applied low-level synchronization primitives for performance and reliability

(More details available in pinned repositories)

BASc in Computer Engineering (Co-op)
University of Ottawa — cum laude

Relevant coursework:

• Embedded Systems & Microcontrollers
• Computer Architecture
• Operating Systems
• Digital Systems
• Computer Network Design
• Real-Time Systems Design

• Writing efficient, predictable, and maintainable firmware
• Understanding systems from silicon to software
• Debugging complex hardware–software interactions
• Building technology that interacts with the physical world

⚡ Always learning. Always building. Especially close to the hardware.