I specialize in the intersection of machine learning and embedded hardware. My work focuses on the practical constraints of edge deployment: minimizing latency, optimizing power, and maximizing throughput on specialized silicon.

I leverage the full potential of local compute—from the Apple Neural Engine to Qualcomm Hexagon DSPs. By architecting software that respects the limitations of physical hardware, I make real-time AI viable in production IoT environments.