- Adaptive and Scalable Systems Lab
- ASSIST Laboratory
- Biomedical Computing and intelligent Systems Lab (BioMeCIS)
- Data Science Lab
- Database Exploration Laboratory (DBXLAB)
- Digital Design Laboratory
- Embedded Systems and Instrumentation Lab
- Human Centered Computing Laboratory (Heracleia)
- Information Security Lab (iSec)
- Information Technology Lab
- Innovative Database & Information Systems Research Lab (IDIR)
- Learning and Adaptive Robotics Laboratory (LEARN)
- Mining and Analysis of Spatio-Temporal Data Laboratory (MAST)
- Multimedia Lab
- 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: ERB 413
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.
Location: ERB 102
Leading Faculty: Farhad Kamangar
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.
Location: ERB306, ERB204
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.
Location: ERB 514
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.
Location: ERB 201/202
Leading Faculty: Roger Walker
Mission: Solve transportation related problems requiring real-time embedded systems, modeling and simulation, statistical analysis and instrumentation.
Location: ERB 313
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: Chengkai Li
Mission: The IDIR Lab in the CSE Department of UT Arlington conducts research in big data management and mining, with current focus on building large-scale human-assisting and human-assisted data and information systems with high usability, low cost and applications for social good. In particular, we work on computational journalism, crowdsourcing and human computation, database exploration by ranking (top-k), skyline and preference queries, database testing, entity query, usability challenges in querying graph data, and Web data management.
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: Junzhou Huang
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.
Location: ERB 513
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.
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.