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About

Mau-Luen Tham is a leading researcher at the forefront of the Internet of Robotic Things (IoRT), a field that merges multi-robot systems with advanced communication networks. His work is pivotal in addressing the critical challenges of resource allocation and mobility management in IoRT, particularly for high-stakes environments like post-disaster management. Tham’s major contributions include pioneering the use of parameterized and twin delayed deep deterministic policy gradient (TD3) reinforcement learning algorithms to dynamically allocate power and radio resources, ensuring quality of service (QoS) for mobile robotic swarms during search and rescue operations. His most cited work, a comprehensive 2023 survey on "Internet of robotic things for mobile robots," has garnered 91 citations, establishing a foundational roadmap for the field by detailing concepts, technologies, and future directions. This paper, alongside his targeted studies on mobility-aware resource allocation, demonstrates his impact in enabling reliable, real-time communication for heterogeneous robots in chaotic environments. Tham’s research is notable for bridging the gap between theoretical reinforcement learning and practical, disaster-resilient IoRT deployments, making him a key figure in advancing autonomous robotic systems for societal benefit.