Faculty research in the Department of Computer Science can be broadly categorized into five cross-cutting thrusts:

  • Computing Foundations and Emerging Technologies
  • Cybersecurity and Privacy
  • Data-Driven Intelligence
  • Networked Computer Systems
  • Software Systems

Our research is supported by more than $5 million in active research grants and contracts from various external funding agencies, such as the National Science Foundation, National Institutes of Health, National Security Agency, Army Research Office, Air Force Office of Scientific Research, Office of Naval Research, and Department of Homeland Security.

The strength of the department’s research is also evidenced in part by nine home-grown NSF CAREER awardees. Among the nine UTSA degree programs recognized in the 2019 Times Higher Education World University Rankings by subject, UTSA’s highest program ranking belonged to Computer Science at 60 in the nation and among the top 250 in the world. The Computer Science research program continues to move up in world ranking: NTU ranking placed it at 108 in 2021 and NSF’s FY20 HERD survey placed the UTSA Computer Science department at the national rank of 57 in R&D expenditures, just below UC Berkeley, and above UT Dallas, Rice, Duke, and Rutgers.

Computer Science faculty and its affiliated research entities (Institute for Cyber Security, Center for Infrastructure Assurance and Security, AI Matrix Consortium, and Open Cloud Institute) have fostered and maintained close ties with research and education partners both inside and outside of UTSA.


Research Areas

Computers are powerful problem-solving devices, but they are not infinitely powerful. As computational power improves over time, we are faced with computational challenges that are growing in both size and complexity. To face these growing challenges, researchers must determine which challenges have solutions that can be computed efficiently and which tasks cannot be computed efficiently.

Answers to these questions can change over time as new technologies are developed in hardware (e.g., quantum and cloud computing) and software (e.g., programming languages and compilers). Researchers in the department approach these critical needs along several fronts such as algorithms, quantum computing, computer architecture, cloud computing, and parallel and distributed systems.

Participating Faculty

Cybersecurity has become a national imperative over the last decade. The number of cyberattacks has increased across all sectors both within the U.S. as well as the world in general. Some estimates place the expected annual cost of cybercrime to exceed $10 trillion by 2025. Given this, the importance of conducting research in various areas of cybersecurity to improve the cybersecurity posture of organizations and nations has increased in importance.

The National Institute of Standards and Technology (NIST) has identified five core functions organizations need to concentrate on in their cybersecurity programs: 1) Identify, 2) Protect, 3) Detect, 4) Respond, and 5) Recover. Each of these core functions provides a rich area for research to improve cybersecurity. Additionally, the introduction of any advances in technology also introduces new cybersecurity concerns. In the last two decades we have seen cybersecurity issues in areas such as cloud computing, wireless networks, autonomous vehicles, cryptocurrencies, artificial intelligence, big data, and the Internet of Things (IoT).

Participating Faculty

The volumes of data produced by humans and machines today significantly outpace humans' ability to absorb, evaluate, and make complicated decisions based on that data. Artificial intelligence/machine learning is the foundation of all computer learning and the future of all complex real-world decision-making under uncertainty.

Our research covers a wide range of topics of this fast-evolving field, advancing how machines reason, learn, predict, plan, and control, while also making them secure, robust and trustworthy. Research covers both the theory and applications of data driven intelligence. This broad area studies artificial intelligence/machine learning theory (such as algorithms and optimization), big data (data management, computation, and analysis), statistical learning (such as inference, graphical models, and causal analysis), deep learning (such as adversarial learning, explainability, and knowledge representation), reinforcement learning, symbolic reasoning, as well as diverse hardware implementations of machine learning.

Participating Faculty

Networked computer systems, from embedded and mobile devices to large-scale high-performance computers, data centers, and cloud computing, have become the backbone of our society’s IT infrastructure, supporting public services, business, scientific innovation, healthcare, and education. The wide application of networked computer systems has made the research on their design, management, optimization, and applications important research areas.

UTSA's Computer Science faculty have a long history of conducting high-impact and innovative research in such systems. Their research involved the fundamental system designs, hardware, algorithms, and optimizations for low-power embedded and IoT devices, parallel, distributed and high-performance computing, cloud computing and data centers, and computer networks. Their research also involves systems support for a wide range of applications, such as web services, AI, big data, healthcare, earth science, virtual/augmented reality, robotics, security, and privacy.

Participating Faculty

Software systems deliver novel computing technologies such as algorithms, intelligence, and analytics, and connect them to the end users. The department's research on software systems covers a variety of research topics towards enhancing software productivity, quality, user experience, scalability, etc. These research projects develop:

  1. Novel features of programming languages and Integrated Development Environments (IDEs) to accelerate software development
  2. Formal methods, program analysis, and testing techniques to systematically reduce software defects and policy violations
  3. Human-computer interfaces based on emerging platforms such as mobile devices and virtual/augmented reality
  4. Scalable software systems over big data

Participating Faculty