Concentration:
- Artificial Intelligence and Machine Learning in Cancer Research
The Ph.D. in Electrical Engineering is a research-intensive program designed to prepare students for advanced careers in academia and research institutions, and for leadership positions in industrial research and development organizations, consulting, etc. Students in the program, under the guidance and in collaboration with their major professors and dissertation committee, pursue original research topics in cutting-edge areas of electrical engineering culminating in a doctoral dissertation.
Major areas of research that can be pursued by Ph.D. candidates currently include: microelectronics (materials and devices of elemental and compound semiconductors, circuit design, modeling, testing, and reliability); communications and signal processing (communication networks, packet switching, satellite communications, communications software, and VLSI for signal processing); systems and controls; solid state material and device processing and characterization; electro-optics, electromagnetic, microwave and millimeter-wave engineering (antennas, devices, systems); and biomedical engineering.
Beginning Fall 2024, the Department of Electrical Engineering in collaboration with the Machine Learning Department of the Moffitt Cancer Institute will begin offering a concentration in Artificial Intelligence and Machine Learning in Cancer Research.
Major Research Areas:
- Artificial Intelligence and Machine Learning
- Automation and Control Systems
- Biomedical Systems
- Communication, Networking, and Signal Processing
- Cyberphysical Systems
- Cybersecurity
- Machine Learning and Artificial Intelligence
- Network Science
- Nanoelectronics and Semiconductor Devices and Systems
- Renewable Energy and Power Systems
- Wireless and Microwave
Current and previous Ph.D. dissertations and M.S. thesis explored areas including computer and wireless networking systems, communications, signal processing, cyberphysical systems, edge computing, 5G mobile communications, social networks, stochastic processes, system modeling, network mining, network analytics, big data analytics, multi-agent systems, cybersecurity, cloud computing, network science, data analytics, wireless and mobile communication networking, artificial intelligence, machine learning, Internet of things, nano-computing, control systems, system integration for industrial applications, industrial Controls & instrumentation, robotics, embedded systems, electromagnetic theory and computational electromagnetics, antenna theory, microwave and millimeter wave device, circuit and system design, wireless systems, radar, RF integrated circuits, biomedical instrumentation and imaging, semiconductor materials for Bio, Nano and MEMS applications, bio/organic materials, VLSI design, renewable energy source grid integration, electric power system modeling and simulation, microgrid technologies, energy and energy storage.
Admission Information
Must meet University Admission and English Proficiency requirements as well as requirements for admission to the major, listed below.
- GRE (with preferred minimum scores of Q greater than 155 (61%), V greater than146 (28%)
- Three (3) Letters of Reference
- Statement of Purpose