Research in Computer Science and Engineering

24 September

Business model would share sensor data

UTA computer scientists investigating framework for sharing sensor data

18 September

Making raw data more usable

UTA computer scientist working to improve data science pipeline

17 August

Computer scientist makes big data more accessible

UTA researcher working to make data more usable and accessible

4 June

Customized treatment for lung cancer patients

UTA teams with UT Southwestern on CPRIT-funded lung cancer project

18 May

A better experience for mobile users

UTA computer scientist earns grant to enhance user experience on mobile devices

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. [Leading Faculty: Hong Jiang, Hao Che]

ACES Lab

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. [Leading Faculty: Jia Rao ]

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. [Farhad Kamangar, Manfred Huber, David Levine, Jason Losh]

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. [Leading Faculty: Jean Gao]

BioMeCIS Lab

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. [Leading Faculty: Gautam Das]

DBX Lab

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. [Leading 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. [Leading Faculty: Jacob Luber]

Health Data Science Lab

Human Centered Computing

Mission: The mission of the Heracleia (heracleia.uta.edu) 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. [Leading Faculty: Fillia Makedon]

heracleia.uta.edu

Human Data Interaction Lab (HDIL)

Mission: The mission of the lab is studying how humans can interact with data to solve open-ended tasks that are easy for humans while difficult for machines by developing artificial general intelligence. [Leading Faculty: Deokgun Park]

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. [Leading Faculty: Cesar Torres]

The Hybrid Atelier

Information Security Lab

The Information Security Lab at UTA conducts research on building a secure computing environment in a hostile world. With an emphasis on software security and malware defense, we seek to develop techniques to find software vulnerabilities and defeat malicious software. [Leading Faculty: Jiang Ming]

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. [Leading 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. [Leading 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. [Leading Faculty: Yingying Zhu]

Machine Learning and Medical Imaging Lab

Mission: Our research focus is on developing efficient methods for analysis of data for various applications in Brain Imaging, Machine Learning and Computer Vision. On the application side, we develop novel methods to facilitate the analysis of neurodegenerative brain disorders (e.g., Alzheimer’s disease (AD)) towards mechanisms for diagnosis, discovering new treatments, and design of new studies. On the technical side, we deal with machine learning algorithms, applied harmonic analysis and statistical image analysis. [Leading Faculty: Won Hwa Kim]

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. [Leading Faculty: Dajiang Zhu]

MIND Lab

Mining and Analysis of Spatio-Temporal Data Laboratory (MAST)

Mission: The MAST Data Lab focuses on mining and analysis of spatial, temporal and spatio-temporal data. Spatio-temporal data is data associated with spatial locations that change over time, which may be slow-changing or rapidly changing (moving objects). Examples of such data include land use, storm tracking, vehicle and cell phone tracking, check-in data used for recommendations, population data, crime data, and fire/flood tracking. Such data typically has geographic (spatial) attributes that change over time. Our research is widespread across analysis, mining, indexing, modeling and storage of spatio-temporal data. Some of our recent research includes spatial location prediction of moving objects, recommendation systems, data integrity and integration, indexing and querying of moving objects, and storm tracking. We recently have introduced neural networks and deep learning methods in our research for better analysis and understanding of the data.

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. [Leading Faculty: Ming Li]

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. [Leading 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. [Leading 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. [Leading 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. [Leading Faculty: Shirin Nilizadeh]

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. [Leading Faculty: Christoph Csallner, David C. Kung, Yu Lei, Allison Sullivan]

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. [Leading Faculty: Vassilis Athitsos]

Vision-Learning-Mining Research Lab

Wireless and Sensor Systems Lab

Mission: WSSLab's mission is to develop novel wearable, mobile, wireless, battery-free sensing and intervention systems for different applications including healthcare, environmental, agriculture, infrastructure management, and so on. We explore and develop new sensors, hardware designs, software techniques, and algorithms so that the developed systems can work reliably in real-world settings despite constrained resources and unpredictable conditions. We build fully integrated, end-to-end systems and demonstrate their scientific advancement through user studies and clinical trials. [Leading Faculty: VP Nguyen]

WSSLab

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. [Leading Faculty: Yonghe Liu]

Undergraduate Applicants

Graduate Applicants

Graduate Certificates

Research Areas

Big Data and Large-Scale Computing

big data analytics and mining, cloud computing, computational journalism, data exploration, data science, distributed computing, environmental and tracking data analysis, parallel algorithms, parallel computing, scalable and distributed graph-processing, scalable memory and storage systems, scientific computing, systems support for big data, warehouse-scale computing

Associated Faculty: Ishfaq Ahmad, Sharma Chakravarthy, Gautam Das, Leonidas Fegaras, Jean Gao, Junzhou Huang, Jacob Luber, Mohammad Atiqul Islam, Hong Jiang, Song Jiang, David Levine, Chengkai Li, Shirin Nilizadeh, Habeeb Olufowobi, Jia Rao, Dajiang Zhu

Biocomputing and Health Informatics

assistive technologies, bioinformatics, computational neuroscience, computer aided rehabilitation, health informatics, human computer interaction, medical informatics

Associated Faculty: Negin Fraidouni, Jean Gao, Junzhou Huang, Jacob Luber, Dajiang Zhu, Yingying Zhu

Computer Networks

anonymity and privacy online, content-centric networking, Internet distributed traffic control, Internet router interface programming, network function virtualization, next-generation networks, opportunistic networks, pervasive computing, secure peer-to-peer systems, sensor networks, software-defined networking, wireless networks

Associated Faculty: Hao Che, Ming Li, Habeeb Olufowobi, Yonghe Liu

Computer Vision and Multimedia

endoscopic vision, gesture recognition, human motion analysis, image processing, neural networks, pattern recognition, robotic vision, sign language recognition, signal processing, video compression, visualization

Associated Faculty: Vassilis Athitsos, William Beksi, Christopher Conly, Alex Dillhoff, Jean Gao, Shawn Gieser, Vamsikrishna Gopikrishna, Junzhou Huang, Jacob Luber, Chris McMurrough, Alexandra Stefan, Cesar Torres

Database and Information Systems

converting data to knowledge, crowdsourcing and human computation, data modeling and summarization, data exploration, data reduction, data warehousing, database testing, deep web and social media mining, entity query, information integration, information retrieval, knowledge discovery, query processing and optimization, real-time databases, searchable file systems, spatial databases, usability challenges in querying graph data, Web data management, XML

Associated Faculty: Sharma Chakravarthy, Gautam Das, Leonidas Fegaras, Negin Fraidouni, Hong Jiang, Chengkai Li

Embedded Systems and Mobile Computing

cyber-physical systems, data acquisition and control, hybrid systems, instrumentation, Internet of Things, mobile and pervasive devices and technologies, mobile applications, modeling and simulation, network simulation and test bedding, real-time systems, reliable and fault tolerant computing, verification and validation, virtual reality, wireless localization, wireless sensor networks

Associated Faculty: William Beksi, Bill Carroll, Hao Che, Mohammad Atiqul Islam, Hong Jiang, Ming Li, Yonghe Liu, Chris McMurrough, VP Nguyen, Habeeb Olufowobi, Cesar Torres

Machine Learning and Data Mining

deep web and social media mining, environmental and tracking data analysis, matrix-based machine learning, neural networks, pattern recognition, similarity-based indexing, social network, spatio-temporal data analysis and mining, sparse learning, statistical and combinatorial algorithms, statistical optimization and data analytic, tensors

Associated Faculty: Ishfaq Ahmad, Vassilis Athitsos, Gautam Das, Alex Dillhoff, Negin Fraidouni, Jean Gao, Vamsikrishna Gopikrishna, Junzhou Huang, Farhad Kamangar, Chengkai Li, Jacob Luber, Fillia Makedon, Shirin Nilizadeh, Deokgun Park, Alexandra Stefan, Carter Tiernan, Cesar Torres, Dajiang Zhu, Yingying Zhu

Robotics and AI

assistive robotics, autonomous robot systems, development of intelligent behavior, endoscopic vision, healthcare robotics, robotic vision, sensor-driven robotics, surgical robotics

Associated Faculty: Ishfaq Ahmad, William Beksi, Vamsikrishna Gopikrishna, Manfred Huber, Fillia Makedon, Chris McMurrough, Deokgun Park, Lynn Peterson, Carter Tiernan, Cesar Torres, Yingying Zhu

Security and Privacy

anonymity and privacy online, malware analysis, mobile device security, secure peer-to-peer systems, usable security and privacy

Associated Faculty: Christoph Csallner, Mohammad Atiqul Islam, David Kung, Ming Li, Yonghe Liu, Shirin Nilizadeh

Software Engineering

agile methods, automated software engineering, automated testing, formal methods, mobile software engineering, object-oriented software engineering, program analysis, program repair, reverse engineering, software cost estimation, software design patterns, software engineering processes, software methodology, software process, software security, testing object-oriented software, verification and validation

Associated Faculty: Christoph Csallner, Mohammad Atiqul Islam, David Kung, Yu Lei, Ming Li, Yonghe Liu, Shirin Nilizadeh, Allison Sullivan

Sustainable Computing

define standards for power-aware hardware and software, design power efficient architectures, energy-aware computing resource provisioning, energy-aware routing in sensor networks, evaluate power and performance tradeoff, green data center architectures, restructure software and applications, spatial indexing for sensor queries

Associated Faculty: Ishfaq Ahmad, Christoph Csallner, Mohammad Atiqul Islam, David Kung, Ming Li, Yonghe Liu, Shirin Nilizadeh