Department of Electrical Engineering and Computer Science

Professors	Nader Namazi, Chair; Lin-Ching Chang; Charles C. Nguyen; Hang Liu
Professors Emeriti
Associate Professors	George Nehmetallah
Assistant Professors	Hieu Bui, Minhee Jun
Clinical Assistant Professors	Matthew Jacobs, Chaofan Sun, Sergio Picozzi
Lecturers	Vincent Cassella; Aysegul Cuhadar; Francis Linehan; Quang Nguyen; Sridava Rao; Kevin Russo; Hanney Shaban; Walter Stimel; Yang Guo; Mohsen Marefat; Babak Parkhideh; Colleen Canovas; Aysegul Cuhadar; Fred Byus; James Turso; Ravi Kalpathy

The Department of Electrical Engineering and Computer Science offers graduate programs leading to the degrees of Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) in Electrical Engineering, Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) in Computer Science, and Master of Science (M.S.) in Data Analytics. Concentrations offered are Machine Learning, Robotics, Data Mining, Communication Systems, Network and Information Security, Sensors and Remote Sensing, Microwave, Optics and Materials, and Signal and Image Processing. The Department also offers graduate certificates in Data Analytics and Power Electronics and Data Analytics.

The faculty is actively engaged in multiple research areas including robotics, autonomous vehicles, artificial intelligence, machine learning, control systems, computer vision, computational informatics, medical image processing and analysis, big data analytics, 3-D imaging, digital holography, metamaterials, image motion detection and estimation, image sequence filtering and restoration, digital communications and classification, wireless communications and networking, mobile computing, Internet of Things, mobile content delivery and video streaming, cybersecurity, software engineering. A majority of the research projects are funded by government agencies and industries such as NASA, the Navy, the Army, NIH, and NSF.

Admission

Students pursuing degree programs should apply for regular admission. The minimum requirement for regular admission to the M.S. program is a bachelor's degree in engineering, science or mathematics from an accredited institution. Students lacking certain requirements for regular admission to the M.S. program can apply for a provisional admission.

Performance of provisional students will be reviewed after two semesters of graduate study for possible transfer to regular admission. The minimum requirements for regular admission to the M.S. program in computer science is a bachelor's degree with undergraduate background in computer science that includes the equivalent of the following topics: data structures, computer organization, software engineering and programming languages, algorithm design and analysis, and discrete mathematics. A student will be provisionally admitted to the M.S. program if he or she has one or more deficiencies. The deficiency courses must be successfully completed before the provisional status is converted to regular status. Admission to the doctoral degree programs is based upon academic performance at the bachelor and master's levels. For other admission requirements, please refer to Admission under Special Regulations.

The minimum requirements for regular admission to the data analytics Master program is a bachelor's degree. The program is intended for those with backgrounds outside of computer science. However, background and/or experience in computer programming and mathematics/statistics are required. A student will be provisionally admitted to the M.S. program if he or she lacks such background/experience. The deficiency courses must be successfully completed before the provisional status is converted to regular status. Students with one or more deficiencies are encouraged to apply for the data analytics certificate program first.

M.S. Program

The M.S. in Electrical Engineering or the M.S. in Computer Science program has two options, non-thesis and thesis. The non-thesis option requires 30 semester credit hours of approved coursework. The thesis option requires 24 semester credit hours of approved coursework plus a thesis comprising 6 semester credit hours of master's thesis guidance. The approved coursework must include at least 18 semester credit hours of approved core courses. The remaining courses must be in engineering and science disciplines and approved by the graduate coordinator of the department. For the thesis option and the non-thesis option, each student must submit a program of study to the department for approval upon entering the program. The program of study must contain a minimum of 30 semester credit hours of approved graduate-level courses.

The core courses for the M.S. in Computer Science must be selected from the courses in the four areas of concentration: computer science foundations, computer systems, software systems, and computing methodologies. At least three semester credit hours are chosen from each of the above areas of concentration.

The M.S. degree program in Data Analytics does not offer the thesis option. The program of study must contain a minimum of 30 semester credit hours of approved graduate-level courses comprising 4 core courses (12 semester credit hours) and 18 semester credit hours of elective courses. The data analytics core courses include Introduction to Data Science and Python, Applied Statistics and Data Analysis, Introduction to Machine Learning, and Applications of Data Analytics and Development.

Doctoral Degree Program

The program of studies is individually tailored to meet the needs of the student and to fit with the department research areas and facilities. Students must pass a comprehensive examination in major and minor areas after completing all required coursework.

The Ph.D. degree requires a minimum of 53 semester hours of formal graduate coursework beyond the bachelor's degree. The major includes at least nine semester credit hours and minor includes at least six credit hours at the graduate levels in one of the listed topic areas. Additional areas that must meet minimum requirements are chosen in consultation with the advisor. For additional degree requirements, see Degree Requirements.

Certificate Programs

Three professional certificates are offered:

Certificate in Data Analytics

This program is designed for those without an engineering or computer science background to acquire mathematics and computer programming skills to extract insight from large data sets in a variety of fields. The certificate requires 12 credits consisting of four (4) three-credit core courses. Students who complete the certificate in Data Analytics may apply for admission to the M.S. program in data analytics, and, if accepted, may count the 12 certificate credits towards their Master’s degree.

The data analytics core courses include Introduction to Data Science and Python, Applied Statistics and Data Analysis, Introduction to Machine Learning, and Applications of Data Analytics and Development.

Certificate in Power Electronics

This program is designed to provide specialized graduate-level education in power electronics. The certificate requires 18 credits, consisting of three (3) four-credit core courses and two (2) three-credit electives. Students who complete the certificate in Power Electronics may apply for admission to the M.S. program in electrical engineering, and, if accepted, may count the 18 certificate credits towards their Master’s degree.

Certificate in Signal Processing & Data Sciences

This program is designed to provide specialized graduate-level education in two related disciplines, signal processing and data sciences, in a practical way. The certificate requires 15 credits consisting of Signal Processing and Data Sciences courses so the students will have interdisciplinary skills to solve real-world problems. Students who complete the certificate in this certificate program may apply for admission to the M.S. program in computer science or electrical engineering, and, if accepted, may count the 15 certificate credits towards their Master’s degree.