Summary
Eugene Valassakis is a Senior Research Engineer and PhD candidate at Imperial College London specializing in robot learning, sim-to-real transfer, and vision-driven imitation learning for manipulation. With nine years of experience spanning research internships at Niantic and Dyson to production roles at Synthesia, he bridges cutting-edge research and deployed systems—his Niantic work led to a shipped real-time hand-mesh tracking feature. He holds dual MSc degrees (Computer Science, Imperial; Machine Learning, UCL) and a BSc in Physics, bringing strong interdisciplinary foundations from optics and physics to ML and robotics. Comfortable across full-stack development, mobile apps, and deep learning research, he combines practical engineering (React Native, production ML) with academic rigor in thesis-driven sim-to-real research. Notably, his background includes hands-on experimental work (graphene research at UC Berkeley), reflecting a rare blend of wet-lab precision and software-first system-building.
9 years of coding experience
4 years of employment as a software developer
Physics, Physics at University of California, Berkeley
Bachelor of Science Physics, Bachelor of Science Physics at University of St Andrews
Doctor of Philosophy - PhD Robot Learning, Doctor of Philosophy - PhD Robot Learning at Imperial College London
University College London
English, French, Greek