Electrical Engineering PhD
Degree Requirements
The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.
The PhD program in Electrical Engineering is divided into two Programs of Study:
- Solid-State, Photonic, and Quantum Technologies
- Signals and Systems
There are requirements common to both Programs as well as additional requirements specific to each Program.
Common Requirements
Course Requirements
- EE requires a minimum of 15 graded courses that count for graduate (TGS) credit, not including ELEC_ENG 590-0. The cumulative grade point average over these graded courses must be a B (3.0 GPA) or higher. Courses that provide zero units of credit do not count toward these 15 units.
- At least 6 of these 15 units must be 400- or 500-level courses.
- At most 2 of these 15 units can be ELEC_ENG 499-0. This course is reserved for projects that are not directly related to the research required for the PhD thesis or for readings in specific subjects for which the ECE Department has no regular courses. ELEC_ENG 499-0 is not intended to replace or augment the required units of ELEC_ENG 590-0.
- All PhD students are required to complete the zero-credit Responsible Conduct for Research Training (GEN_ENG 519-0) during their first year.
- A student's adviser may require more than the minimum number of courses. In such cases, the number of required ELEC_ENG 590-0 units will be reduced accordingly.
Other PhD Requirements
- Teaching Requirement
- Qualifying Examination
- Prospectus
- Dissertation
- Final Exam (dissertation defense)
Additional requirements and processes are detailed in the Electrical Engineering Graduate Study Guide.
Solid-State, Photonic, and Quantum Technologies
Course Requirements
Total Units Required: 15
| Course | Title |
|---|---|
| Core courses in Solid-State, Photonic, and Quantum Technologies | |
| Each student must take 5 of the following courses: | |
| Photonic Information Processing | |
| Fiber-Optic Communications | |
| Nanotechnology | |
| Fundamentals of Electronic Devices | |
| Advanced Electronic Devices | |
| Quantum Semiconductors | |
| Quantum Electronics | |
| Advanced Photonics | |
| Nonlinear Optics | |
| Fundamentals and Applications of Special Relativity | |
| Area-specific courses in Solid-State, Photonic, and Quantum Technologies | |
| Electives must be approved by the student's adviser, and may include the following courses: | |
| Introduction to Communication Networks | |
| Electronic Properties of Materials | |
| Solid State Electronic Devices | |
| Optoelectronics | |
| Superconductivity and Its Applications | |
| Quantum Optics | |
| Computational Electrodynamics | |
| Semiconductor Lasers | |
| Random Processes in Communications and Control 1 | |
| Random Processes in Communications and Control 2 | |
| Distributed Optimization | |
| Introduction to Nanoscale Lasers, Quantum Noise, Photons, and Measurement | |
| Optical Communications | |
| Information Theory and Learning | |
| Selected Topics in Quantum Information Science and Technology | |
| Advanced Communication Networks | |
| Differential Equations of Mathematical Physics | |
Signals and Systems
Course Requirements
Total Units Required: 15
| Course | Title |
|---|---|
| Courses in Signals and Systems | |
| Each student must complete a sequence of courses in an area of specialization according to the recommendation of the adviser. These courses may be in Signals and Systems and other areas. Courses in Signals and Systems may include: | |
| Communications Systems | |
| Introduction to Computer Vision | |
| Introduction to Communication Networks | |
| Digital Signal Processing | |
| Introduction to Feedback Systems | |
| Digital Filtering | |
| Introduction to Digital Control | |
| Digital Communications | |
| Wireless Communications | |
| Special Topics in Electrical Engineering (Cardiovascular Instrumentation) | |
| System Theory | |
| Advanced Digital Signal Processing | |
| Digital Image Processing | |
| Multimedia Signal Processing | |
| Random Processes in Communications and Control 1 | |
| Random Processes in Communications and Control 2 | |
| Distributed Optimization | |
| Signal Detection and Estimation | |
| Optical Communications | |
| Information Theory and Learning | |
| Human Perception and Electronic Media | |
| Advanced Computer Vision | |
| Statistical Pattern Recognition | |
| Deep Learning: Foundations, Applications, and Algorithms | |
| Advanced Communication Networks | |
| Adaptive Filters | |
| Introduction to Nonlinear Control Theory | |
| Deep Reinforcement Learning | |
| Machine Learning: Foundations, Applications, and Algorithms | |
| Advanced Digital Communications | |
| Special Topics in Electrical Engineering (Cardiovascular Instrumentation) | |