Max Robotics — Global Service Robot Directory + US Certification

About

Truong X. Nghiem is a researcher whose work spans autonomous systems, robust control, mobile robotics, and physics-informed machine learning — fields he has advanced through a distinctive blend of theoretical rigor and practical engineering insight. His early contributions focused on the co-design of anytime computation and robust control, addressing the critical challenge of variable execution times in autonomous robot control loops. His 2015 paper on this topic has garnered 31 citations, establishing him as a thought leader in real-time control for safety-critical systems. A significant thread of Nghiem's research centers on mobile robotic sensor networks, where he has pioneered adaptive sampling strategies using Gaussian processes and distributed optimization methods such as proximal ADMM. These contributions enable resource-constrained robot teams to efficiently monitor complex spatial and spatiotemporal phenomena — work with clear implications for environmental sensing and surveillance applications. His investigations into connectivity-preserving informative path planning and real-time distributed trajectory planning further demonstrate his commitment to scalable, multi-robot coordination. More recently, Nghiem has turned toward safe physics-informed machine learning, bridging data-driven modeling with formal safety guarantees for dynamical systems. Across more than 90 total citations, his portfolio reflects a cohesive vision: making autonomous systems simultaneously smarter, safer, and more computationally efficient.