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About

Hung Pham is a leading robotics researcher whose work bridges the gap between theoretical motion planning and real-world industrial automation. His primary research areas include time-optimal path parameterization (TOPP), multi-robot coordination, and contact-rich manipulation. Pham’s most impactful contribution is his pioneering work on large-scale 3D printing using a team of mobile robots, which has garnered over 400 citations and opened new frontiers for construction and manufacturing. He has also made fundamental advances in TOPP theory, developing a novel reachability-based approach that overcomes the limitations of traditional numerical integration and convex optimization methods. His work on critically fast pick-and-place with suction cups addresses a critical bottleneck in logistics automation, while his research on learning manipulation primitives through reinforcement learning offers a path toward more adaptive robotic assembly. Pham’s convex controller synthesis for robot contact provides a rigorous framework for ensuring stability and performance in unstructured environments. Through his combination of theoretical depth and practical application, Hung Pham continues to shape the future of autonomous robotic systems.