Currently
Developing embedded machine learning systems and computer vision applications. Signal processing when the Nyquist theorem permits.
Real-time operating systems provide fascinating constraints for optimization. Determinism is underrated.
Looking for what's next! Take a peek at my resume or cv if you're interested in my journey so far. You should drop me a line if you're working on something interesting. Cheers!
Background
Senior product engineer with experience across embedded systems, full-stack development, and technical leadership. Founded ventures focused on applied machine learning and hardware integration.
Proficient in C/C++, Python, Ruby, JavaScript, Go. Assembly language for those special occasions when abstraction becomes inconvenient.
Based in the rainforests of Vancouver, British Columbia. Laboratory and workshop readily accessible.
Research Interests
The intersection of hardware constraints and algorithmic efficiency continues to yield compelling engineering challenges.
This Site
Custom static site generator built from first principles. Documentation of ongoing projects forthcoming.
‡‡_Selected Works_‡‡
- Bluetooth DSP optimization • Reduced latency from 60ms to 5ms on Xtensa SoC
- Iris biometric system • 95% accuracy at 30m using $30 cameras vs $5K hardware
- Smart City IoT ingestion • 2M+ events/sec with Kafka/Kubernetes in Park City
- Xbox Kinect development • Shipped 8M+ units, gesture and speech input systems
- iOS music platform • 100K+ users, real-time DSP with gyroscope control
- Airport biometric deployment • Led 50+ person team across 15+ airports
- RF threat detection • FPGA-accelerated DSP with adaptive Kalman filtering
- Mobile AI inference • Offline local LLM using iOS and Metal frameworks
- RTOS embedded systems • Zephyr integration on Zynq SoC platform
- Border control kiosks • R&D lab for automated systems with CBSA/DHS
- Real-time remix engine • C++/RtAudio pipeline, $2M seed funding
- Android robotics assistant • ROS + MATLAB/Simulink motion control
- Noise reduction algorithms • Skeletal tracking stability for Xbox Live
- AINR DSP implementation • Ultra-low latency streaming on embedded AI SoC
- Computer vision pipelines • OpenCV-based iris detection and tracking
- IoT sensor networks • C++ control modules for decentralized systems
- Audio DSP middleware • Low-level drivers for AI-driven earbuds
- Passive optical tracking • Rolling-shutter error correction for biometrics
- Edge AI orchestration • TorchScript runtime for privacy-first inference
- Distributed data ingestion • Go/C++ libraries for Smart City deployment