- Abacus Cloud and Edge Systems Lab (ACES)
- Adaptive and Scalable Systems Lab
- ASSIST Laboratory
- Biomedical Computing and intelligent Systems Lab (BioMeCIS)
- Data-driven Research for Security, Privacy and Safety
- Data Science Lab
- Database Exploration Lab (DBXLab)
- Digital Design Laboratory
- Human Centered Computing (Heracleia)
- Human Data Interaction Lab (HDIL)
- Information Security Lab
- Information Technology Laboratory (IT Lab)
- Innovative Database and Information Systems Research Laboratory (IDIR)
- Learning and Adaptive Robotics Laboratory (LEARN)
- Machine Learning and Medical Imaging Lab
- Medical Imaging and Neuroscientific Discovery Laboratory (MIND)
- Mining and Analysis of Spatio-Temporal Data Laboratory (MAST)
- Mobile Computing and Security Lab (MobiSec)
- Multimedia Lab
- Rigorous Design Lab (RiDL)
- Robotic Vision Laboratory (RVL)
- Scalable Modeling & Imaging & Learning Lab (SMILE)
- Software Engineering Research Center (SERC)
- Vision-Learning-Mining Research Lab (VLM)
- Wireless Networks and Systems Lab (WINS)
- XML Lab
Location: SEIR 225
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.
Location: SEIR 331
Leading Faculty: Jia Rao
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.
Mission: The ASSIST Laboratory's focus is on researching and developing technologies to assist the elderly and people with disabilities in their everyday life.
Leading Faculty: Jean Gao
Mission: The mission of the lab is to focus on developing efficient algorithms to solve computational problems in basic medicine and clinics, while making theoretical and fundamental contributions to statistical pattern recognition, machine learning, and computer vision.
Leading Faculty: Shirin Nilizadeh
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: Chris Ding
Mission: Our lab focuses on developing machine learning and big data mining algorithms to solve the applications in health informatics, bioinformatics, computer vision, neuroinformatics, natural language processing, medical image computing, information retrieval, and computational sustainability.
Leading Faculty: Gautam Das
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.
Location: ERB 543
Leading Faculty: Bill Carroll
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: Deokgun Park
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: Fillia Makedon
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.
Location: ERB 316
Leading Faculty: Jiang Ming
Mission: 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.
Location: ERB 514
Leading Faculty: Sharma Chakravarthy
Mission: The mission of this lab is to carry out both fundamental and practically applicable research and development, interact and collaborate with industry/federal agencies for identifying fundamental problems, provide a viable migration path for integrating new techniques/solutions into real-world systems/applications for the management, protection, and analysis of large volumes of data.
Leading Faculty: Chengkai Li
Mission: The Innovative Database and Information Systems Research (IDIR) Lab 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.
Location: SEIR 231
Leading Faculty: Won Hwa Kim
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.
Location: SEIR 231
Leading Faculty: Dajiang Zhu
Mission: Brain Imaging Computing, Computational Neuroscience and Big Data solutions for medical data analysis through computational modeling and machine learning methods.
Location: ERB 514
Leading Faculty: Ramez Elmasri
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.
Location: ERB 101
Leading Faculty: Ming Li
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.
Location: ERB 201
Leading Faculty: Mohammad Atiqul Islam
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.
Location: ERB 413
Leading Faculty: William Beksi
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.
Location: ERB 105B
Leading Faculty: Junzhou Huang
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.
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.
Location: ERB 315
Leading Faculty: Vassilis Athitsos
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 sign language recognition, detection and tracking of complex shapes, large-scale multiclass recognition, and similarity-based retrieval and classification using large databases.
Leading Faculty: Yonghe Liu
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.