I design and build high-speed autonomous robotic systems that achieve real-time performance on affordable edge hardware. My work focuses on extracting maximum efficiency from constrained compute environments through deeply optimized low-level code, careful system architecture, and unconventional engineering approaches.

Rather than relying on expensive GPUs or overpowered infrastructure, I push hardware to its limits — leveraging efficient algorithms, tight integration between perception and control, and resource-aware design to enable capabilities like visual-inertial odometry, 3D SLAM, and learning-based decision-making in real time.

The goal is to make advanced robotics not just powerful, but practical — proving that high-performance autonomy can run on hardware that is accessible, scalable, and deployable in real-world systems.