The Department of Computer Science and Engineering is noted for research and teaching excellence. Its internationally recognized faculty members are engaged in breakthrough research across the leading areas of computer science and engineering.
The department's graduates work at America's leading companies and governmental agencies and in other sectors. UTA's location in the Dallas-Fort Worth metroplex - one of the nation's two most influential technology corridors - and strong relationship with major technology companies such as Raytheon, Lockheed Martin, Nokia, Sabre Holdings and Motorola provide students with outstanding opportunities for internships and jobs.
Our undergraduate CS, CpE and SE programs are ABET accredited.
The paper of Dr. Gautam Das' group and his collaborators, titled "An expressive framework and efficient algorithms for the analysis of collaborative tagging", has been accepted into the VLDBJ special issue on Best of VLDB 2012.
Congratulations to Dr. Gautam Das and his collaborators for winning the "Best Student Paper Award" at the ACM International Conference on Information and Knowledge Management (CIKM) 2013.
Congratulations to Dr. Gian-Luca Mariottini and his student Gustavo Puerto for winning the Best Paper Award at the 6th Pacific-Rim Symposium on Image and Video Technology (PSIVT 2013), in Guanajuato, Mexico.
A UT Arlington multidisciplinary team (PI: Fillia Makedon) will lead a three-year, $1 million National Science Foundation grant project to develop iRehab, a smart rehabilitation system that can adapt and personalize therapy programs based on a patientís needs and constraints.
Congratulations to Dr. Heng Huang (PI) and Dr. Gautam Das (Co-PI) for receiving a grant from NSF titled "Privacy-Preserving Framework for Publishing Electronic Healthcare Records", funded in collaboration with University of North Texas Health Science Center and George Washington University.
Congratulations to Dr. Heng Huang for receiving a grant from NSF titled "Robust Large-Scale Electronic Medical Record Data Mining Framework to Conduct Risk Stratification for Personalized Intervention", funded in collaboration with Southern Methodist University and University of Texas Southwest Medical Center at Dallas.