Max Robotics — Global Service Robot Directory + US Certification

About

Tsun-Hsuan Wang is a leading researcher at the intersection of safe robot learning, computer vision, and soft robotics. His work is unified by a commitment to building intelligent systems that are not only capable but also safe and adaptable to the real world. Wang’s most impactful contribution is **BarrierNet**, a framework that integrates differentiable Control Barrier Functions (dCBFs) into neural network training. This seminal work, with 99 citations, provides end-to-end safety guarantees for neural controllers, a critical step for deploying robots in human environments. In computer vision, he pioneered the **Omnidirectional CNN (O-CNN)** for visual place recognition, a method that robustly handles extreme camera pose variations, accumulating over 87 citations and advancing navigation for mobile robots. Wang has also made significant strides in generative AI, with work on point-to-point video generation, and in the emerging field of soft robotics. His recent projects, including **SoftZoo** and **DiffuseBot**, explore the co-design of robot morphology and control, using generative diffusion models to breed and optimize soft robots for diverse environments. Through this diverse body of work, Wang is shaping a future where robots are both intelligent and intrinsically safe.