You will be at the forefront of the current technology revolution while becoming a high-tech entrepreneur by pursuing a Doctor of Philosophy degree in Electrical Engineering at the University of North Texas.

Graduate opportunities

UNT offers the only Ph.D. program in the region with focus areas that are well-aligned with pressing social, industrial and government needs. In our program, you can concentrate your studies on any of these new, thriving research and business fields.

  • Energy-efficient power-aware antennas and circuit designs in Radio Frequency and Mixed-signal Circuit Design
  • Intelligent wireless sensor networks using sustainable green technology in Communication and Signal Processing
  • Large-scale complex land and airborne networks and cyber-physical systems in Systems and Control

A unique and innovative feature of this program is the integrated entrepreneurship component. We're the first program in the nation to feature this requirement at the Ph.D. level by engaging you in entrepreneurship and the creation of intellectual property and patent development. This in-depth knowledge helps you move your original ideas and results to the marketplace smoothly. You'll earn a minor in Entrepreneurship from the College of Business in addition to your doctoral degree.

Our faculty members are well-known for their expertise, spirit of innovation and emphasis on university/industry collaboration. Their research has been supported by the National Science Foundation, NASA, the National Institute of Standards and Technology, the MITRE Corp. and local industries, among others.

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 academic laboratories, offices and classrooms to facilitate 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 Department of Electrical Engineering is a pioneer in developing project-oriented curricula, giving students the opportunity to apply knowledge to tangible real-world needs.

Additionally, 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.

Research and laboratories

The department houses several state-of-the-art instructional and research laboratories that provide practical and advanced hands-on experiences. They include:

  • Analog, RF and Mixed-Signal Design Laboratory
  • Autonomous Systems Laboratory
  • Communications and Signal Processing Laboratory
  • Computer-Aided Design Laboratory
  • Speech, Music and Digital Signal Processing Laboratory
  • Vision, Robotics and Control Systems Laboratory
  • Wireless Systems and Sensor Networks Laboratory

You'll also have direct access to the Center for Advanced Research and Technology, the UNT Nanofabrication Cleanroom and the Center for Advanced Scientific Computing and Modeling. Some laboratories and instruments from other departments also are available for interdisciplinary work.

More information about these labs is at our website.

Attending UNT

Admission requirements

You must meet the general admission requirements for the Toulouse Graduate School® and a specific set of program requirements:

  • Acceptable GRE or TOEFL scores
  • Personal statement that highlights your background and career plans
  • Three letters of recommendation from professors or employers

Admission is based on a holistic review of your academic background and work experience. Completed admission applications must be received by the department by March 1 for the fall semester and by Oct. 1 for the spring semester.

Degree requirements

The most significant accomplishment of a Ph.D. graduate is an original dissertation that contributes to the advancement of the industry, opening the door to opportunities for new applications. For students entering with a master's degree, the basis of the research reported in the dissertation is supported by an advanced set of courses that includes:

  • 6 credit hours of core electrical engineering courses
  • 9 credit hours of required entrepreneurship courses
  • 6 credit hours of prescribed electrical engineering core electives
  • 6 credit hours of free electives
  • 12 credit hours of dissertation
  • 3 credit hours of individual research

For students entering with a bachelor's degree, the requirements include:

  • 12 credit hours of core electrical engineering courses
  • 9 credit hours of required entrepreneurship courses
  • 12 credit hours of prescribed electrical engineering core electives
  • 18 credit hours of free electives
  • 12 credit hours of dissertation
  • 9 credit hours of individual research

Financial assistance

Several scholarships, teaching fellowships, teaching assistantships and research assistantships are available to help you pursue your graduate degree.

Completed assistantship applications must be received by the department by March 1 for the fall semester and by Oct. 1 for the spring semester.

Information about other financial assistance programs is at the financial aid website.


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; renewable power systems; 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; flexible electronics; 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 system; connected autonomous vehicles.

Xiangnan Zhong, Assistant Professor; Ph.D., University of Rhode Island. Intelligent control and automation; cyberphysical systems; machine learning; robotics.