Major Research Areas

Research in computer vision & graphics in the Department of Computer Science focuses on analyzing and processing visual data such as images, videos, point clouds, polygon meshes, and range/volume data. Computer vision research seeks high-level understanding from digital images and videos while solving challenging problems in object tracking, image clustering, image database indexing, digital terrain modeling, and image fusion. Computer graphics research aims to facilitate efficient visual communication via computational modeling, rendering, and animation of graphical data. The following faculty members are involved in computer vision & graphics research: Sanjiv Bhatia and Henry Kang

The Cybersecurity and Networking Systems group at UMSL carries out research in diverse areas of cybersecurity and networking like the Internet, broadband and other networked systems, security of these networks and network applications, mobile and wireless networks and their security, mobile edge computing, network protocols and network security protocols, secure Internet of things, virtualized networks, cloud computing and management and security of cloud networks. For carrying out collaborative and meaningful research, Cybersecurity and Networking Systems Lab (CNSL) work closely with academia and industry. It focuses on cutting-edge research for providing innovative solutions for future networking and cybersecurity services. The Lab especially focuses on socially relevant research for improving the welfare of the local and global community. The faculties of involved with the lab together have many years of diversified experience. The current faculty members associated with the lab are: Abde Mtibaa, Lav Gupta.

Research in data science in the Department of Computer Science focuses on the design, analysis, and application of computational algorithms for data-centric problems arising in diverse domains. Machine learning and data mining approaches are developed and applied for prediction, classification, regression, and clustering. Linear and non-linear models and hybrid meta-heuristics are explored for data analytics. The following faculty members are involved in data science-related research:  Badri Adhikari, Azim Ahmadzadeh, Sharlee Climer and Uday Chakraborty.

Astronomy Data Science represents a transformative field of inquiry at the intersection of astronomy, data science, and engineering. In the past few decades, the combination of an extensive array of ground-based and space-borne instruments has ushered in an era of unprecedented scientific image data generation. These high-dimensional data hold the keys to unlocking profound insights into our universe, driving impressive advances in various research areas, including high-stakes domains such as Space Weather and Heliophysics. However, harnessing the full potential of this data deluge would not be feasible without the remarkable advancements in both hardware and software. The synergy of cutting-edge technology and innovative data analysis methods has become instrumental in unraveling the mysteries of space, making Astronomy Data Science an indispensable frontier in modern scientific exploration. Agencies such as the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), the Defense Advanced Research Projects Agency (DARPA), and more recently, the United States Space Force (USSF) are some of the key sponsors and stakeholders of this interdisciplinary field. The following faculty members are involved in astronomy data science: Azim Ahmadzadeh.

Our biological sciences research delves into complex computational challenges. We explore protein structure modeling, network modeling, statistics, and clustering in various genetic and disease studies like Alzheimer's, psoriasis, heart failure, vitamin D metabolism, and human genetics. The following faculty members are involved in biological data research: Badri Adhikari and Sharlee Climer