Research

Research prepares students to be problem-solvers and innovators while also supporting the department's crosscutting areas of excellence.

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. The computer science department at Missouri S&T makes use of both its own computer learning center (CLC) as well as university CLCs. The CLC contains a mix of Linux and Windows computing platform. Class sizes are kept small to facilitate student and faculty interactions. Research laboratories provide support for both undergraduate and graduate students. 

Explore our research areas

Research Laboratories

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.

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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).

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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.

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The Theory and Quantum 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. 

For more information contact the Director: Dr. Avah Banerjee banerjeeav@mst.edu 

 

High Performance Computing Lab (HPC Lab) at Missouri S&T is currently engaged in three research projects. In the first project, we are revisiting spatial data analytics on heterogeneous systems comprised of data processing units (DPU), GPUs and CPUs. The DPUs are a new class of programmable processors made by NVidia (and other manufacturers). Similar to a modern smart network interface card, DPUs can be used to filter unnecessary data from overwhelming the CPU and memory bandwidth. DPUs can be used by CPUs to offload computations; thereby reducing the load on CPU and increasing the capability of the compute node. The second project is “Nearest Neighbor Similarity Search for Polygons and Trajectories”. Research thrust of the third project is to design communication-efficient spatial analytics algorithms for data-intensive computations by leveraging Processing-In-Memory (PIM) Paradigm. In this new computational model, code execution happens near DRAM memory instead of CPU.

Research publications are focused on leveraging GPUs and HPC compute clusters for speeding up geospatial analytics workloads like polygon overlay, spatial join, Voronoi diagram, geometric intersection, spatial autocorrelation, etc.

 

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Funded Research Spotlight

Harvesting Idle Resources Safely and Timely for Large-scale AI Applications in High-Performance Computing Systems

Agency: NSF Award #2403398

PI: Dr Seung-Jong Jay Park

The proposed research project aims include investigating idle resources in HPC when running AI applications, harvesting Heterogeneous resources for AI applications safely and timely in HPC and reutilize harvested resources for AI applications in HPC. 

Research Centers

Learn about all our research centers at S&T.  Learn more.