As connectivity becomes ubiquitous and sensors, actuators, and controllers are seamlessly embedded in our daily lives, it is essential to develop general system theories and multidisciplinary design methodologies for emerging networked, multi-agent, and cyber-physical systems. These systems are increasingly autonomous, interconnected, and operate in complex, dynamic environments across diverse domains. Key application areas include high-tech manufacturing, precision agriculture, healthcare, autonomous and cooperative vehicles across land, air, and water, as well as future energy systems such as nuclear fusion. Addressing these challenges requires scalable, adaptive, and intelligent approaches that can handle complexity while ensuring reliability, efficiency, and resilience.

Next-generation engineering systems demand a seamless integration of computation, communication, and control with the physical processes they govern—ranging from thermal, mechanical, chemical, biological dynamics and energy flows and their multi-physics combinations. These cyber-physical systems (CPS) are at the core of autonomous, interconnected, and intelligent technologies, yet the underlying disciplines have traditionally evolved in isolation, limiting their full potential. Bridging this gap requires a new generation of hybrid systems theory that unites control engineering, computer science, and communication theory into a coherent and scalable design framework.

At the same time, the rapid growth of embedded intelligence and connectivity is driving the emergence of large-scale, networked systems that operate in complex and dynamic environments. Addressing these challenges calls for innovative methodologies that enable scalability, adaptability, and real-time decision-making. Our work focuses on developing such theories and translating them into impactful applications, including cooperative and automated driving, precision agriculture and smart farming, advanced thermal and energy systems, hyperthermia for cancer treatment, nuclear fusion, and high-tech manufacturing systems.

With expertise in general systems and control theory, hybrid control surpassing classical control limitations, model predictive control (MPC), neuromorphic and event-triggered control, and the distributed control and estimation of large-scale networked systems, we aim to shape the future of autonomous and complex engineering systems—while offering a dynamic environment for students, researchers, and industry partners to collaborate and innovate.