Simplify& Improve
Building systems that let machines understand the world — and recover when it breaks.
A machine learning engineer drawn to robotics — happiest when building things that work in the real world.
I'm currently a research assistant at Imperial College London, working on how robots perceive, predict, and recover from the unexpected. Before research, I led and shipped products — so I care as much about the system around the model as the model itself.
Less moving parts, sharper results. Simplify, then improve.
AWARE
Detecting anomalies in robotic systems through nothing but a camera — an air-gapped safety net for legacy control systems.
Selected work
Quality-Diversity Reinforcement Learning for Damage Recovery in Robotics
Helping legged robots recover from unexpected damage with better performance and far fewer trials — ReX-MAP-Elites.
Driving Condition-based Energy Management Strategy of Hybrid Vehicles
A driving-profile-aware strategy that lowers the energy consumption of hybrid electric vehicles via multi-agent DDPG.