Research Groups

Research Area/Focuses: Machine Learning, Data Mining.

The goal of the Discovery Analytics Lab is to pursue advanced data mining, machine learning, and predictive modeling research to solve real-life data-intensive problems. The lab collaborates with researchers from the government sector, industry, and academia in designing domain-specific data analytic solutions. Some of the current projects cover modeling of evolving natural languages, automatic hypotheses generation, prediction of crop harvest using evolving hyperspectral imagery data of agricultural lands, and video mining.

Location: CCSB 3.1202F; Contact: Mahmud Shahriar Hossain, Assistant Professor, mhossain@utep.edu.

CYBERSECURITY THROUGH WORKSHOPS, ANALYSIS & RESEARCH (CyWAR)

Research Area/Focuses: Formal Software Methods, Software Assurance, Software Engineering Processes.

The associated Cybersecurity through Workshops, Analysis, and Research (CyWAR) laboratory allows faculty and students to conduct cybersecurity-related research with particular focus on software vulnerabilities. The CyWAR team develops training material to teach techniques for identifying, exposing, and mitigating such software security vulnerabilities. We design, develop, and host hands-on cybersecurity workshops for students and cybersecurity professionals in the El Paso area and beyond.

CyWAR is funded through the Army Research Lab's ARL- South  Open-Campus initiative and is the research arm for the   (CCAA )

Location: Prospect Hall Room 106B; Contact: Salamah I. Salamah, Associate Professor and Chair
Director of Software Engineering, isalamah@utep.edu.

HIGH PERFORMANCE SYSTEMS LAB (HIPERSYS)

The research conducted in the HiPerSys lab, under the direction of Teller and Arunagiri, focuses on performance-enhancing adaptations, both static and dynamic, of high performance computer applications, operating systems, runtime systems, I/O subsystems, and computer architectures. In this case, the term performance encompasses execution time, resource utilization, power and energy efficiency, output accuracy, throughput, and latency guarantees. This research involves workload characterization, algorithm analysis and development, and performance measurement, modeling, and analysis.

Contact: Pat Teller, Professor, pteller@utep.edu.

LINKING KNOWLEDGE ACROSS DISCIPLINES, DATA AND MODELS (iLink)

Research Area/Focuses: Data Integration, Knowledge Graphs, Scientific Workflows and Narratives, Smart Cities, Water Sustainability.

iLink interdisciplinary research aims to improve the efficiency and effectiveness of the discovery, integration, processing and interpretation of scientific data. Our current approaches link human and machine knowledge to address societally-relevant problems that require the integration is data, models, and knowledge from different discipline's and/or organization's perspectives.

Location: CCSB 3.1202D; Contact: Natalia Villanueva-Rosales, Assistant Professor, nvillanuevarosales@utep.edu.

INTERACTIVE SYSTEMS GROUP (ISG)

Research Area/Focuses: Dialog Modeling, Spoken Dialog Systems, Cross-Cultural Communication, Individual Variation in Communication Behaviors, Usability, Language Teaching and Assessment.

The students and faculty of the interactive Systems Group conduct research in models of interaction and the engineering of interactive systems. The Group’s research focuses on the intersection of spoken language and human-computer interaction, applying multiple methods: statistical, linguistic, systems-building, and experimental. Our goal is improving human-human and human-machine communication. We do both fundamental and applied research, using diverse methods including data-collection, model building using machine learning, qualitative analysis, and human-subjects experimentation. Current research projects include using prosodic information to improve speech recognition and using paralinguistic behaviors to improve the realism of embodied conversational agents. To see more about the ISG, check out their website at: https://isg.cs.utep.edu/

Location: CCSB 1.0404; Contact: Nigel Ward, Professor, nigel@utep.edu & David Novick, Professor, novick@utep.edu.

INTELLIGENT AGENTS AND STRATEGIC REASONING LABORATORY (IASRL)

Research Area/Focuses: Artificial Intelligence, Multi-Agent Systems, Computational Game Theory, security, Multi-Agent and Adversarial Learning, Decision Making, Uncertainty and Risk Analysis, Behavior Modeling.

The Intelligent Agents and Strategic Reasoning Lab is engaged in research on how computers can help us to reason about complex, multi-agent environments to make better strategic decisions. We develop new techniques and algorithms that draw on many areas of artificial intelligence, including computational game theory, agent-based simulation, optimization, and machine learning. We are also involved in many exciting real-world applications of strategic reasoning, including scheduling and resource allocation policies for Homeland Security and Border Patrol, game theory for computer network security, and designing trading agents for decentralized energy markets.

Location: CCSB 2.0902C, 2.0902D; Contact: Christopher Kiekintveld, Assistant Professor, cdkiekintveld@utep.edu.

MEDIA-PROPELLED COMPUTATIONAL-THINKING (IMPACT)

The iMPaCT educational research group creates and evaluates educational learning modules that use the programming of low-level graphics to engage students in the exploration of mathematics and various dynamics phenomena. iMPaCT modules have been embedded into into a variety of introductory programming, mathematics, physics, and electrical engineering courses and collaborators include faculty from UTEP’s college of Science, education, and business, El Paso public schools, NYU, and the US Military Academy at West Point.

Location: CCSB 3.1202A, 3.1202B; Contact: Eric Freudenthal, Associate Professor, efreudenthal@utep.edu.

PERFORMANCE-ORIENTED MODELS AND MECHANISMS FOR MULTI-CORE BASED MULTIPROCESSOR SYSTEMS (POM4S)

The POM4S research group is part of the U.S Army High Performance Research Center that aims to apply advanced computational science and engineering to critical Army research challenges. Areas include: stream programming for high performance computing, simulation and modeling to enhance performance of multicore processor systems, high performance optimization, and hybrid optimization schemes for parameter estimation problems.

Contact: Pat Teller, Professor, pteller@utep.edu .

ROBUST AUTONOMIC SYSTEMS GROUP

Research Area/Focuses: Secure High Performance Systems Augmented Perception.

The Robust Systems group has two surprisingly related foci. A recent focus has been the development of wearable devices that augment human hearing. Research to support this focus has included examination of human acoustic perception and extension of our traditional focus on energy efficient, secure, and performant networked computation. Five patents and a tech spinoff have resulted from this work.

Location: CCSB 3.1202A, 3.1202B; Contact: Eric Freudenthal, Associate Professor, efreudenthal@utep.edu.

SOFTWARE SPECIFICATION AND VERIFICATION LABORATORY (SSVL)

Research Area/Focuses: Formal Methods, Programming Languages, Mobile Application.

The goal of SSVL is to advance the practice of developing correct and reliable computer programs. We advocate formal methods -- mathematically-based techniques for the specification, development, and verification of computer programs. Our research includes, but is not limited to, specification languages, verification techniques, and support tools. We are also interested in applying conventional software engineering principles, techniques, and methods to mobile applications development.

Location: CCSB 3.1202G; Yoonsik Cheon, Associate Professor, ycheon@utep.edu.

THEORETICAL RESEARCH AND APPLICATIONS IN COMPUTER SCIENCE (TRACS)

Research Area/ Focuses: Computer Security and Privacy, Optimization, Constraints, Decision Making, Interval Uncertainty.

The focus of TRACS is on development of theory for useful applications. Areas of interest include data (and image) and decision making under uncertainty, constraints, and possible adversity, in particular in relation to online systems and cyber infrastructure. Current applications include the following environmental research, geosciences, biomedical applications, security, and privacy, among others. Special areas of expertise include computer security, constraints, decision making, and interval uncertainty.

Location: 2.0902F, 2.0902G; Contact: Martine Ceberio, Associate Professor, mceberio@utep.edu , Luc Longpré, Associate Professor, longpre@utep.edu, & Vladik Kreinovich, Professor, vladik@utep.edu.

VISION AND LEARNING LAB (VLL)

Research Area/ Focuses: Machine Learning, Computer Vision.

The research goal of VLL is to exploit the potential of machine learning to offer solutions to practical problems for which manual solutions are too difficult to develop. Following this application-oriented philosophy, it has produced results that span a wide area of domains, including Astronomy (galaxy classification, analysis of interacting galaxies), Geology (volcanic eruption prediction, analysis of seismic waves), Neuroscience (image matching and registration), Solar Physics (x-ray and magnetometer data analyses), and Psychology (emotion recognition), among others.

Location: CCSB 2.0902A, 2.0902B; Contact: Olac Fuentes, Associate Professor, ofuentes@utep.edu.

Research Area/ Focuses: Blockchain, Computer and Network Security, Cyber-Physical Systems, Cyber-Threat Information Sharing, Cyber-Risk Assesment and Mitigation, Internet-of-Battlefield Things.

The mission of the TRUstworthy CYBER system (TRUCYBER) lab is to carry out transformative research to advance the security aspects of cyber infrastructure and design/develop decentralized trustworthy systems by addressing the underlying fundamental security challenges. Being a strong believer of cross-disciplinary research, TRUCYBER lab rigorously incorporates distributed and decentralized design methodologies, such as blockchain, to enable trust and provenance in the next generation cyber systems. Members of this lab exploit concepts form distributed systems, network theory, mechanism design, human society inspired evolutionary models, and behavioral dynamics to design secure yet robust solutions that are fundamental to IoT and cyber physical systems. The topics being pursued include, but not limited to, designing lightweight consensus models in Blockchain, provenance and identity management in large scale cyber physical systems, cyber-resiliency in Internet-of-Battlefield-Things (IoBT) environment, and enabling coordinated vulnerability disclosure (CVD) for cyber risk management.

Location: CCSB 3.1202E; Contact: Deepak Tosh, Assistant Professor, Email: dktosh@utep.edu

This research lab applies some of the most advanced software analytics tools, techniques, and methodologies to understand the fundamentals of software design and reengineering. It aims to address some key persistent software engineering challenges including optimizations of software design, software maintenance and sustainability. By improving our understanding of the fundamentals of software design, the group makes contributions to international standards, such as UML, and contributes to key open source projects, including Eclipse, Umple and Susereum. The group explores opportunities to reduce software and data complexities, and the complexity of the tools used for software development and data management. This involves exploration of novel design languages and methodologies and investigations to evaluate their effectiveness. This research often results in direct contributions to industrial software design and modeling tools, such as Papyrus.

Research Area/ Focuses: Network Security, Reverse Engineering, Autonomous Defense

The CyberRIG focuses on practical autonomous cybersecurity advancement and tackles issues using a 3-pronged approach. Cybersecurity events involve the recreation of known incidents and issues to establish a ground truth - these are developed in the forms of workshops and hackathons that are then hosted for partners, the community, and other students. Research helps to advance the state of the art by identifying and building real solutions to real problems. Finally, the group transitions research into technology in the form of tools that can aid defenders.

Research Area/ Focuses: Cybersecurity, Usability and Privacy, Human Factors and Cognitive Modeling

The goal of Psyber Security Lab is to engage in interdisciplinary research broadly focused on cybersecurity using Machine Learning, Game-Theory, Human Experiments, and Cognitive modeling. The current research projects at PyberSec Lab include two major themes: Cyber Defense focusing on cyber deception, recommendation systems such as intrusion detection systems and information sharing dilemma among cyber defenders, and Cyber Education focusing on the development of educational games for K-12 students, development of training for users to prevent them from various attacks such as Phishing and Spear Phishing.

The research conducted in AIRL focuses on the development of applied deep learning technologies to solve problems in the domains of computer vision, natural language processing, human-interaction modeling, and content generation. Current research focuses include automatic music generation, multimodal conversation modeling, and weight initialization.

Research Area/Focuses: Information Retrieval and Integration, Data Analytics, Cybersecurity , Game and Gamification

We work in the broad areas of data science, specially information retrieval and integration, data mining, prediction, and recommendation. We use data science concepts to address computational challenges in application areas of cybersecurity, health informatics, and gaming.

Research Area/Focuses: Software Engineering, Artificial Intelligence, Machine Learning , Data Mining , Model-Driven Systems, Engineering

This research group is focused on predicting software evolution using a variety of approaches, including software quality predictive analysis, with the goal of enhancing upfront software designs and enabling effective continuous design refactoring. This research creates “Digital Twins” to enable the analysis of multiple possible futures for these systems.

Research Area/Focuses: Agile Software Development, Data Integration, Data Management, Computer Science Education.

The goal of this lab is to utilize industry standard software development techniques to improve functionality and reliability of systems. Through the integration of data, software systems can be dynamically produced and maintained for continuous development. This lab aims to focus on fundamental research techniques to integrate data and software system development.

Location: TBD; Contact: Daniel Mejia, Visiting Assistant Professor; dmmejia2@utep.edu

The goal of the Edge Computing Lab is to explore architectural and algorithmic challenges to distributing data and computation across a range of computing systems from edge devices to intermediate (i.e., "fog") nodes to cloud computing systems. A further goal is to apply the research findings to enable IoT applications such as air quality monitoring and pedestrian safety.

Research Area/Focuses: Algorithmic Fairness, Data-Driven Security, Software Reliability.

The goal of RISC is to improve the reliability, security, and fairness of traditional as well as modern data-driven software systems. Currently, the lab focuses on projects at the intersection of software engineering, machine learning, and cybersecurity such as: (1) the application of ML for software testing and debugging; (2) reliable, accountable, and fair machine learning; (3) program analysis for software reliability and security; (4) probabilistic programming and statistical methods for robustness and fairness.

Research Groups

Connect With Us

Location

Donate