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Welcome to the Control, Intelligence, Resilience in Networks and Systems (CIReNS) lab website! Our lab at University of Texas at Dallas is geared around the field of control of networks, network optimization, and applications in Cyber-Physical Systems (CPS), focusing on developing innovative strategies to manage and enhance the performance of interconnected systems. Investigating resilience and robustness in distributed systems and networks is crucial for ensuring the stability and reliability of these complex infrastructures, especially in the face of unforeseen challenges. Another key area of research at our lab involves control-based approaches for graph machine learning, where the intersection of control theory and machine learning is leveraged to extract valuable insights from networked data. Additionally, the study of multi-robot coordination aims to improve the efficiency and cooperation among autonomous agents. An overarching interest of our lab lies in applied graph-theoretic problems and network science, where the application of graph theory principles is employed to address real-world challenges and optimize network structures for various practical applications.