Research in Computer Science and Engineering

Students performing research in computer science and engineering

Research Labs in Computer Science and Engineering

Our department has a number of teaching and research laboratories, centers and other facilities that support its educational and teaching mission. Its internationally recognized faculty members are engaged in breakthrough research across the leading areas of computer science and engineering.

Abacus Cloud and Edge Systems Lab (ACES)

Mission: At the ACES Lab, we focus on modeling, analysis, and resource management for large-scale parallel and distributed computing systems. In particular, we are interested in developing highly scalable, user-centric resource allocation solutions for cloud and edge computing. To this end, user-utility-based, distributed, joint compute-network-and-storage resource allocation solutions with provable convergence and optimality properties are sought. [Lead Faculty: Hong Jiang, Hao Che]


Adaptive and Scalable Systems Lab

Mission: The Adaptive and Scalable Systems Lab focuses on building computer systems that are adaptive to changing workloads, scalable for platform growth, and capable of providing quality-of-service guarantees and service differentiation. We combine performance analysis at the application, OS, and hardware levels with machine learning techniques to characterize the complex behaviors of computer systems. [Lead Faculty: Jia Rao]

Arlington Computational Linguistics Lab (ACL2)

Mission: This lab seeks to advance knowledge on natural language processing and knowledge engineering, with particular interest in the interdisciplinary research that empowers other scientific fields. [Lead Faculty: Kenny Zhu]


ASSIST Laboratory

Mission: The ASSIST Laboratory's focus is on researching and developing technologies to assist the elderly and people with disabilities in their everyday life. [Lead Faculty: Farhad Kamangar, Manfred Huber, David Levine, Jason Losh]

Autonomous and Intelligent Systems Lab

Mission: The Autonomous and Intelligent Systems Lab operates in partnership with the Automation and Intelligent Systems Division of the UT Arlington Research Institute’s Division of Automation and Intelligent Systems.  We conduct research in machine learning, robotics and autonomous systems to solve real-world problems.  Focuses include navigation and control algorithms for a wide variety of autonomous vehicles, assistive robotics for people with disabilities and mobility impairments, computer vision for environmental monitoring, and learning from demonstration for safe cooperative robotics. [Lead Faculty: Nicholas Gans]

Biomedical Computing and intelligent Systems Lab (BioMeCIS)

Mission: Developing efficient algorithms to solve computational problems in basic medicine and clinics, while making theoretical and fundamental contributions to machine learning, data mining, pattern recognition, and computer vision. [Lead Faculty: Jean Gao]

BioMeCIS Lab

Biomedical Computing and intelligent Systems Lab (BioMeCIS)

Mission: At Cyber Guard Research Lab, our mission is to safeguard emerging platforms, medical applications, web frameworks and other widely-used technologies by uncovering software vulnerabilities and developing robust defense solutions. Through the utilization of cutting-edge tools powered by program analysis, machine learning, natural language processing, and LLM, we diligently identify potential threats and propose innovative strategies to fortify the cyber-physical ecosystem. Our commitment lies in ensuring the safety and security of these platforms, ultimately contributing to a more resilient digital landscape. [Lead Faculty: Faysal Hossain Shezan]

Cyber Guard Research Lab (CGRL)

Data Security and Privacy Lab

Mission: Develop novel methods to enable information security and privacy in modern communication systems that are robust against computationally unbounded adversaries, with a focus on solutions that are resistant against quantum-capable adversaries. [Lead Faculty: Remi Chou]

Database Exploration Lab (DBXLab)

Mission: At Database Exploration Lab (DBXLab), we seek to investigate fundamental research issues arising in Big Data. Our research encompasses diverse areas such as data mining, information retrieval, data uncertainty and probabilistic methods, approximate query processing, data summarization, data analytics and data exploration of hidden web databases, social and collaborative media. [Lead Faculty: Gautam Das]

Digital Design Laboratory

Mission: The DDL supports the design and prototyping of digital systems for educational and special purpose applications employing legacy and current design tools and implementation technologies. [Lead Faculty: Bill Carroll]

Health Data Science Lab (HDSL)

Mission: building computational tools and frameworks that at massive scale allow for cancer imaging data to be 1) contextualized in the oncology clinic to improve patient outcomes and 2) leveraged at the bench to augment drug discovery efforts. The lab also focuses on developing computational and statistical methods for handling high throughput `omics data such as single cell transcriptomics/spatial transcriptomics (10X Visium & Chromium), spatial proteomics (CODEX), and calcium imaging. [Lead Faculty: Jacob Luber]

Health Data Science Lab

Human Centered Computing

Mission: The mission of the Heracleia ( lab computational innovations in the areas of Human Computer Interaction (HCI), Pervasive Computing, healthcare services for disabilities, data analytics for behavior monitoring applications, assistive robotics, and computer aided rehabilitation. [Lead Faculty: Fillia Makedon]

Hybrid Atelier

Mission: The Hybrid Atelier is a creative technology research makerspace, serving as a nexus between the Arts, Engineering, and Sciences, with the mission of re-imagining, inventing, and supporting what creativity and making will look like 20 years from now. The atelier focuses its efforts in the areas of Human-Computer Interaction, Design, Physical Computing, Digital Fabrication, and Augmented Environments. [Lead  Faculty: Cesar Torres]

The Hybrid Atelier

Immersive Efficient Computing and Communication Lab

Mission: The Immersive Efficient Computing and Communication (IMEC2) lab is dedicated to developing efficient technologies for future immersive computing and communication. Specifically, we have been focusing on mobile systems and networks, including virtual, augmented, and mixed reality (VR, AR, and MR), digital twins, etc., over 4G/5G and beyond. Our overarching mission is to enable technologies for mobile systems and networks in another decade, extending beyond form factors such as VR/AR headsets. [Lead Faculty: Jiayi Meng]

Immersive Efficient Computing and Communication Lab

Information Technology Laboratory (IT Lab)

Mission: The mission of this lab can be summarized as: a) carry out both fundamental and practically applicable research & development, b) interact and collaborate with industry/federal agencies for identifying fundamental problems, and c) provide a viable migration path for integrating new techniques/solutions into real-world systems/applications. [Lead Faculty: Sharma Chakravarthy]

Information Technology Lab

Innovative Data Intelligence Research (IDIR) Laboratory

Mission: The Innovative Data Intelligence Research (IDIR) Laboratory conducts research in several areas related to big data intelligence and data science, including data management, data mining, natural language processing, applied machine learning, and their applications in computational journalism. The lab's current research focuses on building large-scale human-assisting and human-assisted data and information systems with high usability, high efficiency and applications for social good. Particularly, the ongoing research projects include data-driven fact-checking, exceptional fact finding, fake-news detection, usability challenges in querying and exploring graph data, knowledge databases, and data exploration by ranking (top-k), skyline and preference queries. The lab started the inter-disciplinary research in computational journalism at UTA in 2010 and has since been at the frontier of this nascent field. [Lead Faculty: Chengkai Li]

IDIR Laboratory

Machine Learning and Computer Vision for Clinical Applications

Mission: We focus on customizing machine learning and computer vision techniques to solve various clinical problems including computer aided diagnosis using multi-modal and multi-source datasets such as medical imaging, EHR and clinical reports data collected from different institutes or hospitals; smart patients surveillance system using multiple censoring dataset collected from cameras, wifi and radar. [Lead Faculty: Yingying Zhu]

Medical Imaging and Neuroscientific Discovery Laboratory

Mission: Our research in MIND mainly focuses on the discovery of fundamental principles of brain structural and functional architectures and their relationship, via brain imaging, computational modeling and machine learning methods. We are interested in the interaction between Artificial Intelligence (AI) and Human Intelligence (HI): Using Deep Learning to facilitate the analysis and interpretation of brain data; Applying neuroscience knowledge to design more efficient Deep Learning architectures. We also have strong interests in applying the discovered principles, theories and methods to better understand neurodevelopmental, neurodegenerative and psychiatric disorders including Autism, Alzheimer’s disease, and Major Depression, among other brain conditions. [Lead Faculty: Dajiang Zhu]


Mobile Computing and Security Lab (MobiSec)

Mission: The mission of the lab is to develop effective mechanisms to address security/privacy challenges, improve system performances, and explore novel applications in mobile computing. [Lead Faculty: Ming Li]

Mobile Machine Intelligence Lab (Noodle Lab)

Mission: Our primary objective is to conduct rigorous research and development focusing on integrating software and hardware co-design principles in the AI ecosystem. The aim is to create trustworthy, efficient, and adaptable AI models that can operate effectively within the limited resources of on-device platforms, then democratizing AI to real-world on-device applications. Our research draws upon methodologies from mathematical tools, machine learning, computer architecture, and high-performance computing. We specifically build the general framework of software/hardware co-design for efficient and trustworthy AI based on higher-order tensor decomposition and optimization algorithms, then apply the corresponding AI models to on-device applications. [Lead Faculty: Miao Yin]

Rigorous Design Lab (RiDL)

Mission: Today’s computer systems have been continuously evolving to catch up with the demands of modern society. The technological progress is stretching the boundaries of what is possible, creating new unprecedented operational challenges. To that end, we focus on enhancing computer systems with secure and efficient designs through rigorous investigation and evaluation. [Lead  Faculty: Mohammad Atiqul Islam]

Robotic Vision Laboratory (RVL)

Mission: The focus of the RVL is on the challenge of applying computer vision to robotics and automation. We believe that the ability to visually perceive, understand, and respond to the complex world around us is crucial for the next generation of robots in manufacturing, transportation, construction, infrastructure inspection, environmental monitoring, agriculture, healthcare, space exploration, defense, and the home. [Lead Faculty: William Beksi]

Robotic Vision Laboratory (RVL)

Scalable Modeling & Imaging & Learning Lab (SMILE)

Mission: In SMILE, we focus on developing scalable models and algorithms for data-intensive applications in high performance computing. In particular, we focus on advanced algorithms, software and systems for statistical learning, imaging informatics and computer vision. Our interest is to develop efficient algorithms with nice theoretical guarantees to solve practical problems involved large scale data. [Lead Faculty: Junzhou Huang]

Security and Privacy Research Lab

Mission: In this lab, we conduct data-driven research to understand online security, privacy and safety, and to develop novel techniques and frameworks for improving them. Our research is interdisciplinary and spans widely across multiple areas, from data science and social computing research to traditional security and privacy research. [Lead Faculty: Shirin Nilizadeh]

Security and Privacy Research Lab

Software Engineering Research Center (SERC)

Mission: The mission of the Software Engineering Research Center (SERC) is to conduct cutting-edge research in various areas of software engineering, including software design, specification, analysis, verification, and testing. [Lead Faculty: Christoph Csallner, David C. Kung, Yu Lei, Allison Sullivan]

Transformative Wireless Systems and Technology (TWiST) Lab

Mission: At the Transformative Wireless Systems and Technology (TWiST) Lab, our commitment is to lead the way in pioneering groundbreaking advancements in wireless communication and systems. Through innovative research initiatives spanning areas such as Networked Robotics, Spectrum Learning, Open-RAN, and beyond, we aspire to redefine the capabilities of wireless systems. Our multidisciplinary team operates at the forefront of technology, integrating AI, ML, AR/VR, and other cutting-edge fields to develop transformative solutions. With a steadfast focus on practical applications and tangible real-world impact, we endeavor to shape the future of wireless technology and facilitate its seamless integration with intelligent robotics. [Lead Faculty: Debashri Roy]


Vision-Learning-Mining Research Lab (VLM)

Mission: The VLM lab is a research lab at the Computer Science and Engineering Department of the University of Texas at Arlington. At the VLM lab we are conducting research in the areas of computer vision, machine learning, and data mining. Areas of focus include gesture and sign language recognition, human motion analysis, detection and tracking of complex shapes, large-scale multiclass recognition, and similarity-based retrieval and classification using large databases. [Lead Faculty: Vassilis Athitsos]

Wireless Networks and Systems Lab (WINS)

Mission: The WINS lab, directed by Dr. Yonghe Liu, focuses on challenging issues in wireless networks. The group's research spans both theoretical study and practical system design and development. Our current research projects include novel architecture for sensor networks, routing and buffer management for delay tolerant networks, networking issues in opportunistic networks, and mobile social networks. [Lead Faculty: Yonghe Liu]

Research Areas

Our faculty conduct research in six general areas: Artificial Intelligence, Big Data and Data Science, Computer and Network Systems, Human-Computer Interfaces, Security, and Software Engineering. Each general area is divided into more specific focus areas.

Faculty Research Areas

Research Areas

Our faculty conduct research in six general areas: Artificial Intelligence, Big Data and Data Science, Computer and Network Systems, Human-Computer Interfaces, Security, and Software Engineering. Each general area is divided into more specific focus areas.

Faculty Research Areas