Where would you like your graduate degree to take you? Will you develop a trailblazing, intelligent wireless sensor network that can detect biological or chemical agents? A new way to manage acoustic signals in speech, ultrasound, hearing aids or music? Or something entirely new?
The Department of Electrical Engineering at the University of North Texas offers coursework leading to a Master of Science degree in Electrical Engineering. With this degree, you'll be well-positioned for an accomplished career in tomorrow's tech-driven world.
With small class sizes, you'll work closely with distinguished faculty members to solve complex problems faced by government, businesses and consumers. You also can take advantage of the invaluable contacts we've developed with leading companies and corporate partners.
Our cutting-edge courses and research areas range from artificial intelligence and coding theory to speech-driven facial animation and very-large-scale integration design.
You can engage in advanced high-tech collaborative research supported by grants from the National Science Foundation, NASA, the U.S. Army Research Laboratory and others in the industry.
Engineering classes and research are conducted at Discovery Park, a 300-acre research facility located five miles north of the main campus and served by a free shuttle. It brings together laboratories, offices and classrooms to maximize the potential for creativity, collaboration and technological innovation.
The College of Engineering constantly assesses its degree programs with an eye on tomorrow's marketplace. The college is a pioneer in developing project-oriented curricula that allow you to apply knowledge in tangible, real-world applications.
UNT provides services unique to the needs of graduate students. The Graduate Writing Support Center can help you with writing a thesis, dissertation or class paper, and the Research and Statistical Support Services team can help you achieve your research goals using cutting-edge research technology tools and statistical analysis. A Thesis Boot Camp and other specialized workshops are available through the Toulouse Graduate School®. Many of the workshops are available online for your convenience.
We’re committed to excellence in teaching and the discovery and application of knowledge through research and creative activities. The department houses several state-of-the-art instructional and research laboratories that provide practical and advanced hands-on experiences. Some laboratories and instruments from other departments also are available for interdisciplinary work.
You must meet the general admission requirements for the Toulouse Graduate School® and a specific set of program requirements:
Admission is based on a holistic review of your academic background and work experience. If your undergraduate degree isn't in electrical engineering, you'll need to complete leveling courses as determined by your graduate advisor.
You can earn scholarships based on your academic performance. The department and faculty research grants also provide teaching and research assistantships. Only master's students who select the thesis option are eligible for teaching or research assistantships.
Completed assistantship and admission applications must be received by the department by March 1 for the fall semester and by Oct. 1 for the spring semester.
Miguel F. Acevedo, Regents Professor; Ph.D., University of California, Berkeley. Ecological and environmental modeling and monitoring; global climate change and variability; landscape and forest ecology; environmental systems and sustainability.
Colleen Bailey, Lecturer; Ph.D., University of Buffalo. Communication systems with a focus on signal and image processing.
Shengli Fu, Professor and Department Chair; Ph.D., University of Delaware. Coding and information theory; wireless communications; aerial communication and networks.
Oscar N. Garcia, Professor; Ph.D., University of Maryland. Speech-driven facial animation; speech recognition; artificial intelligence and knowledge-intensive reasoning; cognition and complex systems.
Parthasarathy Guturu, Associate Professor; Ph.D., Indian Institute of Technology (India). Wireless sensor networks; computer vision; data fusion; computational intelligence.
Anupama B. Kaul, Professor; Ph.D., University of California, Berkeley. 2-D materials; energy harvesting devices; flexibleelectronics; nanodevices; nanomaterials; nanotechnology.
Xinrong Li, Associate Professor; Ph.D., Worcester Polytechnic Institute. Statistical signal processing theory and applications; algorithms design and real-time implementation; wireless communications and networks; wireless channel measurement and modeling.
Yuankun Lin, Professor; Ph.D., University of British Columbia. Photonic band gap materials; photonics; laser optics; laser-matter interaction; Raman spectrum; fiber optics and sensors; holographic lithography and two-photon lithography.
Ifana Mahbub, Assistant Professor; Ph.D., University of Tennessee, Knoxville. Low-power integrated circuit design; analog and mixed-signal circuit design; impulse radio UWB transmitter for biomedical applications.
Gayatri Mehta, Associate Professor; Ph.D., University of Pittsburgh. Low-power VLSI design; reconfigurable computing; system-on-chip design; embedded computing; computer architecture.
Kamesh Namuduri, Professor; Ph.D., University of South Florida. Image/video processing and communications; information assurance; wireless sensor networks.
Hua Sun, Assistant Professor; Ph.D., University of California, Irvine. Information theory and its applications to communications, networking, privacy, security and storage.
Murali Varanasi, Professor; Ph.D., University of Maryland. Computer arithmetic; coding theory; VLSI design.
Tao Yang, Assistant Professor; Ph.D., Washington State University. Networked control systems; smart grid; cyberphysical systems; distributed control/optimization with application to power systems; connected autonomous vehicles.
Xiangnan Zhong, Assistant Professor; Ph.D., University of Rhode Island. Intelligent control and automation; cyberphysical systems; machine learning; robotics.