Both undergraduate and graduate students have the opportunity to do research alongside expert computer science faculty in the areas of distributed embedded systems, machine learning, data mining, and software engineering. Or, you can choose the interdisciplinary route, doing research beside faculty in various engineering disciplines. In fact, compsci graduate students often work in large group settings with faculty from departments across campus, examining advanced research problems in bioinformatics, homeland security, embedded systems, and virtual reality. Cooperation between students and faculty at this advanced level is a hallmark of the computer science research program.
The mission of the Applied Computational Intelligence Laboratory is for students to gain many advantages, including collaboration in a work environment, continued involvement with research, the positive influence of role models and mentors, and, more often than not, an opportunity to publish. (Publishing is required for all graduate students.) The ACIL welcomes small and large business cooperative ventures in intelligent computing.
The mission of the CReWMaN Laboratory is to conduct innovative research in networking (core, wireless, sensors), mobile and pervasive computing, distributed and grid computing, privacy and security, biological networks, and social networks. This is accomplished by creating a stimulating learning environment through teaching, research, mentoring and service excellence, with focus on teaching cutting-edge courses and establish multi-disciplinary collaborations.
The mission of the Critical Infrastructure Protection Laboratory is to research in advanced methods of security applied within the realm of critical cyber and cyber-physical infrastructures. The focus is on the use of rigorous mathematics through formal methods to create and analyzer fault-tolerant and secure real-time distributed computing systems applied to critical infrastructure protection. The laboratory supports undergraduate, graduate, and faculty researchers. Students in the laboratory participate in the campus Center for Academic Excellence in Information Assurance and Research, the Intelligent Systems Center, and the Center for Research in Energy and Environment.
The mission of CPHS laboratory is to conduct cutting-edge research to design and develop smart and trustworthy cyber-physical human systems. Our focus is on multi-agent trust (e.g. due to security/privacy concerns, selfish interaction, social discrimination and lack of transparency), machine learning, and human decision modeling in the context of diverse application domains such as transportation, mining and healthcare. The laboratory is also equipped with a prototype transportation testbed which is equipped with autonomous robots (e.g. Nvidia Jetbots), Jetson Nano cards to mimic road side units and diverse sensors (e.g. cameras, EEG headsets to monitor driver’s mental state).
The mission of Polaris Lab is to develop high-performance and scalable middleware for large-scale data management, storage, and analytics on cutting-edge computing systems. Driven by the actual needs from multiple science domains, research in the Polaris lab aims to address the perform issues raised by the big data challenges in real-world applications via deep collaborations with computational scientists. The research products are widely used in multiple DOE laboratories and will be validated on current and next-generation supercomputers including Summit, Aurora, and Frontier.
The mission of the Securing Artificial Intelligence and Internet of Things (SAINT) Laboratory is to explore the synergy between AI and IoT, design robust machine learning algorithms under non-ideal or even hostile conditions, and safeguard vulnerable IoT systems against security attacks. Research is conducted on the interplay between Artificial Intelligence and Internet of Things, adversarial machine learning, and IoT security.
The mission of the Statistical Machine Learning Lab is to obtain methods for autonomous systems that solve novel use-inspired research problems. Our focus is on using statistical techniques to theoretically analyze the performance of proposed methods and to quantify the hardness of the problem. We utilize algorithmic techniques to reduce their computational cost and make them feasible for real-world applications. Several problems we work on are of an interdisciplinary nature and involve collaboration both within and outside the Computer Science department. We provide a supportive and creative environment for undergraduate and graduate students to engage in current machine learning research.
The TAQIS lab focuses on foundational areas in Computer Science and Quantum Information Science. The main focus areas are Quantum Algorithms for near-term hardware as well as theory of Quantum Computation.
The mission of the Web and Wireless Computing (W2C) & Pervasive and Mobile Computing Laboratory is designed to carry out cutting edge research in different aspects of data management (security, compression, replication, caching, query processing, aggregation, fusion) in wireless networks and cloud computing environment. Our focus is on scientific research to advance the state of art in these areas. The current projects are supported by NSF, DOE, ARL, ARO, AFRL, NIST, UM System, etc. The current researchers in the lab are pursuing their PhD/MS degree in different areas of interest. The lab is well-equipped with over 50 3.2 Ghz PCs, 5 Dell Server, linux machines, laptops etc. The lab also has sensor network test-beds consists of Crossbow sensor motes like Telosb, Mica2 and Missouri S&T motes. Lab has also developed a DTN testbed for disseminating information securely for battlefield environment.
The mission of the Wireless Networks and Intelligent Systems (WNIS) Laboratory is to study and investigate new wireless technologies for next-generation wireless intelligent networks. Our focus is on advancing the fundamental understanding of current-existing wireless networking and digging new spectrum technologies for future wireless networks. We also design and develop new efficient and flexible intelligent systems, with a transdisciplinary and software-defined approach.
Learn about all our research centers at S&T. Learn more.