As a research scientist turned head of engineering, I have made foundational contributions to AI-driven video compression at Deep Render. I joined the company to work on the core video compression model, where I played a pivotal role in shaping its architecture and maintaining the codebase. My work involved engaging with cutting-edge research, combining techniques from generative AI and neural network inference acceleration for edge deployment. In my current role as head of engineering, I manage a team of 20 engineers responsible for directing the training, deployment, and optimization of AI-based video codecs on edge platforms and consumer devices, ensuring our technology can operate efficiently in power-constrained environments while delivering state of the art compression performance.
Before my current position, I obtained a PhD degree in Mathematics at the University of Oxford where I studied higher dimensional geometry of a specific class of manifolds that commonly appear in string theory.
