Centers and Labs
Three dedicated research spaces are available for projects affiliated with SYSE. The Applied Systems Lab is managed by Dr. Ruths; and the Center for Control Science and Technology is directed by Dr. Yurkovich; The Laboratory for Dynamics and Control of Nanosystems (LDCN) and the Quantum Device Center are supervised by Dr. Reza Moheimani; the Laboratory for Control, Intelligence, and Resilience in Networks and Systems is managed by Dr. Waseem Abbas.
Center for Control Science and Technology (CCST)
The Center for Control Science and Technology (CSST) at the University of Texas at Dallas is an umbrella organization of researchers in varied disciplines that meet the challenges of a rapidly changing, technology-driven, global society.
The CCST was formed in 2011 to accommodate a growing group of researchers focusing on systems, control science and technology. Dr. Yurkovich initiated the center’s development and was later named its director by the Dean of the Jonsson School.
The primary purposes for this umbrella organization include:
- Developing and organizing relevant curriculum
- Fostering joint proposals and research
- Recruiting excellent graduate students
- Promoting UT Dallas systems and control research
Beyond traditional areas of systems and control theory, the CCST supports activities in operations research and encompasses application areas including robotics, healthcare systems, energy systems, automotive systems and biomedical systems.
CCST researchers partner with businesses in the Dallas-Fort Worth Area’s diverse industry climate. Major industries include defense, financial services, information technology and data, life sciences, semiconductors, telecommunications, transportation and processing. Among these businesses, 21 have been featured on Fortune magazine’s top 500 companies in the United States.
In addition to conducting interdisciplinary research that enhances relevant control systems technology, CCST practitioners host seminars taught by other leaders to deliver high-quality education to students and professional engineers.
Applied Systems Lab
The Applied Systems lab is in ECSW 1.460 and ECSW 2.445 and houses several testbeds for studying the safety and security of automation, such as process control systems, robotic systems, and autonomous vehicles. These systems are used to research the impacts that cyber-attacks can have on control systems.
Nova is an undergraduate research team under Professor Justin Ruths developing a research-focused and open source self-driving vehicle. While companies have made great strides in autonomous driving, it has become difficult for academic research to participate due to the proprietary nature of the software that runs these systems. Nova aims to provide research groups with a solution that can not only be understood and operated by an academic research lab, but also be deployed in real-world test vehicles.
The Nova team is purposefully composed of undergraduates. The project offers undergraduates an unparalleled opportunity to engage with theory, algorithms, and their practical implementation on real systems and hardware. Students investigate technical literature to find appropriate methods, evaluate and integrate community libraries, and develop code to implement new algorithms. Students must collaborate, coordinate, and project plan with multidisciplinary team on a project that spans across many timescales.
Laboratory for Dynamics and Control of Nanosystems (LDCN)
Laboratory for Dynamics and Control of Nanosystems (LDCN) is a multi-million dollar state-of-the-art research facility dedicated to the advancement of nanotechnology through innovations in systems theory and control engineering. The main goal of research in the laboratory is to develop methodologies, technologies, and the necessary instrumentation for fast and accurate interrogation and manipulation of matter at the nanoscale. Laboratory is equipped with state-of-the-art equipment for measurement, characterization and real-time control of high-precision mechatronic systems. LDCN’s multidisciplinary research team pursues a dynamic and active research program that maintains a solid systems and control focus on a variety of emerging applications in nanotechnology.
Center for Atomically Precise Fabrication of Solid-State Quantum Devices
Among many implementations of quantum technology, there is a particular interest in solid-state quantum devices. These require fabrication processes with accuracy and resolution well beyond the capability of the commercial tools presently used in the semiconductor industry, or even the best available research tools ever reported in the scientific literature. To meet the requirements of solid-state quantum device fabrication, the Quantum Center at UT Dallas brings together a collaborative team of researchers to develop atomically precise fabrication technologies, based on the Hydrogen Depassivation Lithography (HDL) method. This approach promises orders of magnitude improvements in resolution and precision over existing technologies.
Control, Intelligence, and Resilience in Networks and Systems Laboratory (CIReNS)
The CIReNS Laboratory conducts research at the intersection of control theory, network science, and machine learning, addressing fundamental challenges in modern networked systems. We aim to design and analyze resilient and efficient networked systems that can operate reliably and effectively in complex and dynamic environments. A central theme of our work is understanding how network structure (topology) influences system dynamics and leveraging this insight to enhance performance and resilience. Our research focuses include:
(1) Controlling Networks: We develop scalable methods to control large-scale networks (such as robots, drones) by directly influencing only a small subset of agents. Our goal is to uncover principles for efficient network control under resource constraints to tackle complex systems.
(2) Network Resilience: We explore how networks can maintain functionality despite disruptions, including faults, failures, or adversarial attacks. We investigate the fundamental limits of resilience, examine resilience-performance tradeoffs, and design innovative strategies for reliable operation in critical environments.
(3) Control for Learning: We leverage insights from network control theory to improve the performance of graph machine learning algorithms that analyze and learn from data with complex interdependencies.
In addition to these themes, we apply our research to address network resource allocation problems using advanced tools from graph theory and discrete geometry. Our work bridges theoretical advancements with practical applications, solving challenges in networked cyber-physical systems, multirobot systems, and social networks. The CIReNS Laboratory is equipped with state-of-the-art facilities, including a motion capture system, a fleet of TurtleBots, Jackal robots, Crazyflies, Oura rings for behavioral sensing, and high-performance computing resources. These facilities empower students and researchers to experiment and test their theories in real-world scenarios.