Yiwen Lu 陆逸文
I work on autonomous systems that learn to act without being explicitly programmed. I started with the mathematics of adaptive control: how to safely operate systems you don't fully understand. Then robot manipulation, capturing how humans use their hands. Now I'm building AI agents that reason and act in the world.
Work
Eko
I helped build Eko, a framework for AI agents that work across browser and desktop. Most frameworks target one or the other; Eko handles both. Designed for real deployment: you can pause, inspect, and resume agents mid-task.
DexCanvas
At DexRobot, my team built DexCanvas: 70 hours of human hand demonstrations expanded to 7,000 hours through physics-validated simulation. Unlike vision-only datasets, we capture contact forces, which is essential for learning manipulation that actually works.
Learning-Based Control
My PhD asked: how do you control a system you don't understand, safely, while learning? I developed controllers with a "circuit breaker" that guarantees safety and learns efficiently. Validated on real hardware, not just simulations.
Background
Harvard SEAS
Visiting scholar
Tsinghua
PhD + BE, Control