Hello, I'm Chenggang

My life goal is to endow robots with the agility, dexterity, robustness, and autonomy of animals and humans, enabling them to operate in diverse settings from human spaces to unstructured field environments. I aim to design robots that understand tasks, interpret environments, are self-aware, learn from creatures, and execute their duties so elegantly and efficiently that they can eventually outperform their teachers.

Numerical optimal control and reinforcement learning are the main focuses of my research. I believe perception, prediction, and motion planning are inherently linked, and that AI problems cannot be solved by treating them merely as information processing challenges. Instead, physical robots must gain knowledge and intelligence through direct interaction with the physical world.

Although the world is full of chaos, it is governed by the principle of optimality. This principle underlies thermodynamics, fluid mechanics, relativity, quantum mechanics, particle physics, string theory, optics, and more. Great scientists have given us the mathematical tools, and Deep Learning plus acceleration hardware have given us the computational power to solve them in our generation.