MS in Computer Engineering
Available Scholarships
Scholarships and Assistantships
All applicants are encouraged to contact faculty members with areas of research matching their interest.
To find out about the Graduate Assistantships application deadline, check with the Department’s main office.
Educational Background
Mission
The MS in Computer Engineering provides students with the knowledge, skills, and research competencies necessary for pursuing professional careers or doctoral studies in the field of computer engineering.
Program Educational Objectives
The MS in Computer Engineering provides a learning-centered environment where accomplished faculty share their experience and knowledge with students so that graduates will:
- Be capable of integrating undergraduate fundamentals to solve complex electrical and computer engineering problems. They will have comprehension of advanced topics in several areas, with depth in at least one area.
- Have the ability to conduct research or execute development projects and to proficiently document the results.
Student Outcomes
Graduates are expected to be able to demonstrate the ability to:
- Apply knowledge from undergraduate and graduate education to identify, formulate, and solve new and complex electrical and computer engineering problems
- Plan and conduct an organized and systematic study on a significant topic within the field
- Communicate both orally and in writing at a high level of proficiency in the field of study
Admission Requirements
Applicants for admissions to the program must hold a degree of Bachelor of Science in Engineering or Bachelor of Engineering, from a recognized university. A minimum cumulative Grade Point Average (GPA), on a 4.0 scale, of 2.75 and a minimum Major GPA of 2.75, or their equivalent, is required.
Bachelor of Science in Engineering holders, from a 120-credit program, must complete an additional 12 credits of engineering courses prior to their enrollment in the Masters program. No credit toward the graduate degree is given for these courses.
Candidates must submit complete applications by following the steps available at Graduate Applicants | Apply to LAU. The application must include:
- Official transcripts.
- Curriculum vitae.
- One letter of recommendation from a full-time faculty who is familiar with the applicant’s academic history.
Students with a Bachelor of Engineering may transfer up to 18 credits from their undergraduate BE program, provided that the transferred credits correspond to graduate courses in the MS in Computer Engineering and that the student has scored at least a grade of “B” on each of these courses. Credits transfer is governed by the Academic Rules and Procedures for graduate programs.
Curriculum (30 credits)
Required Courses (9 credits)
COE 899 Thesis (6 credits)
GNE 798 Research Methods (3 credits)
Elective courses (21 credits)
MS in computer engineering students must choose their elective courses (21 credits) from the table below according to the following criteria:
- MS COE students must take four different courses (12 credits) from COE tracks; the remaining three elective courses (9 credits) can be picked from any track (COE or ELE).
- Students wishing to specialize in a specific concentration can choose at least two of their elective courses from that concentration area (AI, Hardware, Software, Communications etc.)
Track | Concentration Area | Course | |
---|---|---|---|
Number | Title | ||
ELE tracks | Communication and Signal Processing | ELE731 | Optical Fiber Communication |
ELE735 | Information and Coding Theory | ||
ELE772 | Digital Image and Video Processing and Compression | ||
Integrated Circuits, Electronics, and Control | ELE757 | Simulation of Electronic Circuits | |
ELE799D | Topics: Biomechatronics | ||
Electric Power and Energy Systems | ELE721 | Electrical Energy Storage Systems | |
ELE724 | Faulted Power Systems | ||
ELE726 | Renewable Energy | ||
ELE729 | Design and Operation of Smart Grids | ||
COE tracks | Computer Hardware | COE723 | High Performance Computer Architecture |
COE725 | VLSI Design | ||
COE729 | Testing for Digital Integrated Circuits | ||
Computer Software and Networks | COE745 | Information Security | |
AI Systems Engineering | COE743 | Intelligent Data Processing and Applications | |
COE744 | Intelligent Engineering Algorithms | ||
COE746 | Machine Learning | ||
COE747 | Deep Learning | ||
COE748 | Large Language Models | ||
COE774 | Computer Vision and Deep Learning | ||
No Track | COE755 | Queuing Theory | |
ELE753 | Reliability Evaluation of Engineering Systems |
Student Research
MS students in computer engineering conduct research under the close supervision of qualified faculty members with diverse technical backgrounds. The research work is culminated by publishing a thesis that contributes to the advancement of knowledge in various disciplines of computer engineering. As an MS student, you will have access to the state-of-the-art equipment, computing tools, software and online databases.
Some of the recent and ongoing projects include research on deep learning, machine learning, robotics, image processing, smart grids, renewable energy, information security, 5G communications and wireless networks.
Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
A Stackelberg Game Inspired Model of Real-Time Economic Dispatch with Demand Response
Low-Light Image Enhancement for Object Classification using Deep Learning
Circuit-Averaged Modeling of Non-Ideal Low-Power DC-AC Inverters
Unsupervised Feature-Based Visualization Tool Applied on Medical Data