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Master of science in computer engineering

The MSCPE program was introduced to provide advanced and specialized education in computer engineering for practicing engineers, researchers and professionals working in academia and industry.  It was established to provide an opportunity for practicing engineers to advance their careers. The programs provide sufficient breadth and depth of knowledge to satisfy the requirements of the national and international accreditation bodies, and thus allowing our graduates the opportunity to practice different computer engineering topics. The MSCPE program also contributes towards the development of advanced computer engineering research in UAE.  In order to compete in the highly competitive industrial world of today, it is not enough to transfer knowledge and technology from outside, but it is also necessary to grow and promote research using local talent.


1. Admission Requirements

The rules and regulations of the College of Graduate Studies are articulated in two publications: the Graduate Studies Bylaws and the Executive Regulations for the Master's Programs. Based on these rules and regulations, the Graduate Studies Committee in the Department of Computer Engineering grants regular enrollment for applicants to the MSCPE program who satisfy the following academic qualifications and criteria:

a. The student must hold a bachelor's degree from a university recognized by the MOHE at the UAE with a minimum or equivalent CGPA of 3 on a 4-point scale. Students with a CGPA of 2.5 to 2.99 may be admitted conditionally provided that they register maximum (6) credit hours in the first semester of their study and obtain a "3" average. If he/she does not meet this requirement, the student is entitled to register only 3 credit hours in the second semester. The student will be expelled from the program, if he/she does not obtain "3" average at the end of the second semester.

b. The bachelor's degree must be in a major that enables the student to study the Master's program.

c. A student may be admitted in a program other than his/her major upon the recommendation of the Departmental council, the College council and the approval of the University's Graduate Studies Council. Additionally, the Department shall determine the prerequisite courses the student must take in a period not to exceed two semesters or a maximum of 24 credit hours. Such prerequisites must be taken before the Master's courses. No prerequisite courses shall be counted in the calculation of the CGPA or the time limit set for graduation. For each 12 prerequisite credits taken by the student, a semester shall be added to the time limit set for completing the program

d. Attendance in the bachelor's degree must not be less than 75% of the total hours required for graduation. The Council may admit students with degrees obtained by distance learning in special circumstances.

e. Meeting the TOEFL condition:

1)  Students in programs taught in English: The student must obtain 550 points on the TOEFL test or 6 on the IELTS.

2) Students in programs taught in Arabic: These majors do not require the TOEFL test, but the student is required to take and pass an English language course as a prerequisite. The student, however, may be exempted from this prerequisite if he/she scores 400 points on the TOEFL.

3) Native speakers of English shall be exempted from the TOEFL Test if the language of instruction in the first degree was English, and the degree was obtained from a country where English is the formal language. Exempted are also students who graduate from academic institutions where English is the medium of instruction provided that they have scored a minimum of 500 points on the TOEFL Test or equivalent upon joining the undergraduate program.

The Departmental council may, with the approval of the University's Graduate Studies Council, stipulate additional conditions for admissions and re-admissions.

2.1  Program Goals

The program goals are:

1. Provide graduate students with the advanced knowledge and skills required to solve research oriented technical problems in Computer Engineering.

2.  Provide graduate students with an advanced grasp of theories and the insight required to enhance their professional careers and/or to pursue further higher education and lifelong learning.

3. Fulfill the future needs of the Research and Development (R&D) for various industries and establishments of the United Arab Emirates (UAE) and the region at large.

4.  Promote a sense of leadership with emphasis on scholarship and professional ethics.

2.2  Program Learning Outcomes

Upon the successful completion of the program, students should be able to:

  1. Apply advanced theories and methodologies in the field of computer engineering.
  2. Propose advanced engineering solutions with sustainability factors in global, economic, environmental, and societal context.
  3. Communicate effectively in oral and written forms to present complex and diverse problems to professional audience.
  4. Value the principles of professional ethics issues and develop fair and valid judgments in contemporary contexts.
  5. Function on multidisciplinary teams with management and leadership capabilities.
  6. Design and conduct experiments/simulation for research.
  7. Use advanced engineering tools to analyze and interpret data.

3.  Program Structure

Table 1 - shows the structure of the MSCPE.

Table 1. Program Components

Master Program Table 2.jpg 

3.1   Program Requirements

  1. Compulsory courses (9 credit hours)
  2. Elective Courses (15 credit hours)
  3. Thesis or Project (9 credit hours)

Table 2 and Table 3 below list the Compulsory and elective courses for the MSCPE.

Table 2 : Compulsory Requirements ​ ​ ​
Course Code Course Title Credit Hours Pre-requisite
1502501
Engineering Research Methodologies  3 Grad Standing
1502502
Optimization Methods in Engineering
3
Grad Standing
1502503
Applied Mathematics for Engineering
3 Grad Standing
1502590
Graduate Seminar
0
Grad Standing
1502599
Master Thesis
9
Grad Standing

 *Students must complete 12 hours of course credits before registering the thesis.


Table 3 : Elective Courses ​ ​ ​
Serial Course Code Course Title Credit Hours Pre-requisite
1 1502504
Modeling and Simulation
3 Grad. Standing
2 1502509 Special Topics in Computer Engineering 3 Grad. Standing
3 1502520
Computer Architecture 3 Grad. Standing
4 1502522 Distributed Syst. & Cloud Comp 3 Grad. Standing
5 1502525 Reconfigurable Computing 3 Grad. Standing
6 1502530
Real-Time Embedded Systems 3 Grad. Standing
7 1502534/0402535 Neural Networks & Applications 3 Grad. Standing
8 1502539 Special Topics in Computer Application 3 Grad. Standing
9 1502540 Computer Networks 3 Grad. Standing
10 1502543 Network Security and Cryptography 3 Grad. Standing
11
1502549
Special Topics in Computer Networks 3 Grad. Standing
12
1502550/0402554 Integrated Circuit Fundamentals 3 Grad. Standing
13
1502554/0402551 Analog IC Design
3 Grad. Standing
14
1502559 Special Topics in Microelectronics and VLSI 3 Grad. Standing
15
1502560 Security of E-Services 3 Grad. Standing
16
1502562 Security Attacks and Defenses 3 Grad. Standing
17
1502563 Hardware Security 3 Grad. Standing
18
1502575
Independent Studies in Computer Eng. 3 Grad. Standing
19
1502630
Computational Intelligence & Knowledge Eng. 3 Grad. Standing
20
1502631/0402633
Robotics
3 Grad. Standing
21
1502640/0402643
Mobile Computing
3 Grad. Standing
22
1502642/0402663
Computer Vision
3 Grad. Standing
23
0402540
Communication Systems Eng.
3 Grad. Standing
24
0402543
Information Theory
3 Grad. Standing

 

4. Study Plan

Table 4 shows the semester by semester study plan for the MSCPE.

Table 4.1 : First Year(Fall Semester)​ ​ ​
Course Code Course Title Type Credit Hours
1502503
Applied Mathematics for Engineering Compulsory
3
1502501
Engineering Research Methodologies
Compulsory
3
15025xxx
Elective 1
Elective  3

Total

9


Table 4.2 : First Year(Spring Semester)​ ​ ​
Course Code Course Title Type Credit Hours
1502502
Optimization Methods in Engineering Compulsory
3
15025xxx
Elective 2
Elective 
3
15025xxx
Elective 3
Elective  3

Total

9


Table 4.3 : Second Year(Fall Semester)​ ​ ​
Course Code Course Title Type Credit Hours
15025xxx
Elective 4 Elective
3
1502590
Graduate Seminar
Compulsory 
0
1502599
Master Thesis
Compulsory  3

Total

9


Table 4.4 : Second Year(Spring Semester)​ ​ ​
Course Code Course Title Type Credit Hours
15025xxx
Elective 5 Elective 
3
1502599
Master Thesis
Compulsory
6

Total

9


1502501 / 0402501 Engineering Research Methodologies (3-0:3)
This course covers students learning activity on how to apply the engineering research process and methods of inquiry to solve engineering problems; doing literature review in the areas of interest, this involves critiquing current research work. Students learn legal and ethical issues related to protecting and exploiting research, more specifically, intellectual Property rights. They will also learn how to communicate findings in specific engineering formats to specialist audiences. Students will learn basic project management and teamwork skills in addition to research ethics. Course project will allow the students to apply research methodology components on research problems of their choice. Students are expected to present and defend their research proposals.


1502502 / 0402502 Optimization Methods in Engineering (3-0:3)
The course deals with formulation, solution and implementation of optimization models such as linear programming, dynamic programming, integer programming, quadratic programming, convex programming, geometric programming and unconstrained optimization for analyzing complex systems problems in industry.


1502503 / 0402500 Applied Mathematics for Engineering (3-0:3)
This course covers solution of linear equations, Eigenvalue eigenvector decomposition, Special functions, Complex analysis, Fourier analysis, Laplace transform, Introduction to partial differential equations. The course deals with various examples from engineering disciplines.


1502504  Modeling and Simulation (3-0:3)
Elements of modeling and simulation, Simulation techniques,  Review of probability theory basics, Discrete-event simulations, Design of simulation models, Generation of pseudo random numbers, Testing Random Number Generators (RNG), Random variates generation, Commonly used distributions in modeling & simulation, Statistical analysis of the output of simulations, Verification and Validation, Simulation languages and Packages, Applications of modeling and simulation to computer science and engineering. A term paper and a final project are required from each student.


1502520 Computer Architecture (3-0:3)
This course covers the fundamentals of computer design, Instruction set design principal Pipelining, Instruction-Level Parallelism, Dynamic Scheduling Multi-processor, Thread-level Parallelism, Memory-Hierarchy Design, Virtual memory, Buses, I/O and RAIDs.


1502522 Distributed Systems and Cloud Computing (3-0:3)
This course covers Parallel algorithms, Multi-processing, Process level multiprocessors, interconnection, and processing elements, Task partitioning & allocation, Inter-process communication, Message passing protocols, Performance evaluation measures, Scalability and maintainability, Proto-types & commercial distributed systems, Cloud Computing & Virtualization concepts, Cloud architecture & Components, Cloud infrastructure, Cloud Services, Cloud Controllers, User interface & Cloud Dashboard, OS images, Cloud Data Storage and Management.


1502525 Reconfigurable Computing (3-0:3)
The course reviews the main components of the VHDL, introduces the reconfigurable architecture such as FPGAs,  explains how to use the IP cores to implement the reconfigurable Computing applications. In addition to reconfigurable case studies. ​


1502530 Real-time Embedded Systems
(3-0:3)
The course covers the architecture of real time embedded systems, design and construction of instruction set of embedded system, selected case study: Design software/hardware of MIPS processor, and the task scheduling algorithms. 


1502534 / 0402554 Neural Networks and Applications
(3-0:3)
This course includes introduction, background and biological inspiration. The course covers survey of fundamental methods of artificial neural networks: single and multi-layer networks; perceptions and back propagation. The course deals with associative memory and statistical networks, supervised and unsupervised learning, merits and limitations of neural networks, and applications.


1502539 Special Topics in Computer Applications
(3-0:3)
Advanced and emerging topics are selected from the area of Computer Applications. Contents of the course will be provided one semester before it is offered.


1502540 Computer Networks (3-0:3)
This is a first, graduate-level course in computer and communication networks. The course focuses on network mechanisms, such as error-control, routing, subnetting, congestion control, and resource allocation. The course covers also aspects of network protocols and technologies, such as Ethernet, WiFi, IP, TCP and UDP. Fundamental concepts of network delay and delay-bandwidth-product calculations will be covered. In addition, the general concept of packet switch architectures will also be covered.


1502543 Network Security and Cryptography
(3-0:3)
This course covers theory and practice of cryptographic techniques used in computer security. Topics include Encryption (secret-key and public-key) and privacy, Secure authentication, Cloud Security and Electronic commerce, Key management, Cryptographic hashing and data integrity (Digital signatures), Internet voting and Trust systems, Blockchains and Zero-knowledge protocols.


1502549 Special Topics in Computer Networks
(3-0:3)
This course covers advanced topics in Computer Networks. The contents will vary depending on the selected topics in the computer network research field.


1502550 / 0402554 Integrated Circuit Fundamentals
(3-0:3)
This course covers basic integrated circuit design & process technology, Design of simple analog & digital IC components in Bipolar & MOS technology. Modeling & simulation of integrated circuits, SPICE simulation, Fundamentals of Photo-lithography, Basic integrated circuit layout techniques, Applications & types of IC chips.


1502554 / 0402551 Analog IC Design
(3-0:3)
The course serves as an advanced course for electronics students in analog integrated circuits (IC) design. The course will focus on conventional and modern analog building blocks for analog signal processing in BJT and MOS technology both in continuous time and discrete time applications. The course include analog multipliers, the op-amp applications in active filters, op-amp non-idealities, Nonlinearity cancellation of the MOS transistors, MOS-C Continuous time filters, Switched-C Circuits, and High frequency analog blocks ( ex: Current Conveyors and current feedback amplifiers).


1502559 Special Topics in Microelectronics and VLSI
(3-0:3)
Advanced and emerging topics are selected from the area of Microelectronics and VLSI Contents of the course will be provided one semester before it is offered.


1502560 Security of E-Services
(3-0:3)
This course covers security aspects of electronic systems and wireless networks. Topics include e-commerce, e-government, e-services, biometrics-based security, wireless networks security, Virtual Private Networks (VPNs), intrusion detection systems, and computer network security risk management. A refresher of fundamentals of e-security concepts including e-security tools, like Public key cryptosystems, and trust management systems. A term paper and a final project are required from each student.


1502575 Independent Studies in Computer Engineering
(3-0:3)
The student is expected to carry out an independent study on a current issue in a selected area of Computer Engineering. This study is to be supervised by a faculty member and requires the approval of the department. The student is required to produce a formal report, which will be evaluated by his instructor. 


1502590 Graduate Seminar
(3-0:3)
Students are required to attend seminars given by faculty members, visitors, and fellow graduate students. Each student is also required to present a seminar outlying the research topic of the master thesis.


1502599 Master Thesis
(3-0:3)
The student has to undertake and complete research topic under the supervision of a faculty member. The thesis work should provide the student with an in-depth understanding of a research problem in computer engineering. It is expected that the student, under the guidance of the supervisor, will be able to conduct research somewhat independently, and may also be able to provide solution to that problem. 


1502630 Computational Intelligence and Knowledge Engineering
(3-0:3)
This course covers concepts, design, implementation of computational intelligence involving integration of different methodologies: intelligent database management systems, rule-based systems, neural-type systems and fuzzy systems for heuristic problem solving, diagnostics, risk analysis and decision support; decision trees, reasoning techniques. 


1502631 / 0402633 Robotics
(3-0:3)
This course deals with the modeling and control of open-chain serial manipulator and their basic applications. Topics include an overview of robotic systems, serial manipulator, forward kinematic, inverse kinematics, Jacobian and forward velocity kinematics, inverse velocity kinematics, motion control and trajectory design. 


1502640 / 0402643 Mobile Computing
(3-0:3)
The course includes: the convergence of wide-area wireless networking and mobile telephony to support ubiquitous access to information, anywhere, anyplace, and anytime. Topics include Mobile-IP, Ad-hoc networks, Local connectivity, 3G-wireless networks, Approaches to building mobile applications (e.g., mobile client/server, thin client, proxy architectures, and disconnected operation) and mobile e-commerce. 


1502642 Computer Vision
(3-0:3)
This course covers image formation, image representation and display, image processing (smoothing, enhancement, edge detection, filtering), convolution, Gaussian masks, scale, space and edge detection, Feature extraction, Hough transforms, stereoscopic vision and perspective projection, motion, active contour models. 


0402540 Communication Systems Engineering
(3-0:3)
This course covers the fundamental of communication system engineering. It provides an overview of probability and random processes, autocorrelation, spectral density and noise in linear systems. Additionally, it covers PAM and PCM systems, detection of binary and M-ary signals in Gaussian noise, matched filter and correlator receivers. Moreover, the course deals with error performance for binary and M-ary systems, pulse shaping, band pass modulation and demodulation techniques, channel capacity and other selected topics in digital communications.


0402543 Information Theory
(3-0:3)
This courses focuses on the fundamental limits on data compression, and on transmission over communication channels. The course topics include the information measures of entropy and mutual information, source coding theory, data compression, Huffman coding, Lempel-Ziv codes, arithmetic codes, the rate distortion theory, the channel capacity theory, and Gaussian channels.


5.  Graduation Requirements

Before graduation, student should complete all graduation requirements that include:

-  Completing successfully all courses of the program.

-  Completing successfully the thesis and/or essays as specified in the curriculum.

-  Obtaining a minimum cumulative GPA of 3.0.

-  Publishing a paper in the student's specialization in a refereed journal or a conference proceedings provided that the student    is the main author of the paper to be reviewed by two independent reviewers.


Special Admission Requirements
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