Master of Science in Electrical Engineering
An electrical engineering master's degree that merges technology, engineering, and science and applies them to practical, industrial, and business applications.
Program Overview
Rapidly developing global technologies are changing the way we live. The Master of Science (MS) in Electrical Engineering at RIT Dubai combines theoretical fundamentals and practical applications in this dynamic field and educates students in the practices, methodologies, and cutting-edge techniques used in electrical engineering including Artificial Intelligence. Students will build on experience of engineering and customize a specialty of their choosing while working closely with electrical engineering faculty in a contemporary and applied research area.
The MSEE degree requires the completion of 30 credits divided between core courses, electives (which may be selected according to a focus area), and thesis/graduate paper. The degree requirements are shown in the program chart.
Students can customize their degree plan to meet their preferences under the general MSEE degree option as shown in the leftmost column of the program chart. The chart also demonstrates how students may be able to select a specific subset from the available electives to focus their studies in AI Systems with application to smart energy, control/robotics, or communications if enough of the relevant courses are offered in the desired track during their duration of study. However, the declaration of a focus area is not required and is used for advising purposes to help students initiate research in a focus area, but not required for degree completion and selected focus areas won’t appear on students’ transcripts. All students will be certified against the general MSEE degree requirements. Note that the core courses are common to all options and that the focus area courses are a subset of the general MSEE elective courses.
For the general MSEE option, students are required to take three core courses (EEEE-602, 707, and 709) and choose 5, 6, or 7 elective courses based on their choice of thesis, graduate paper, or comprehensive exam, respectively.
For the MSEE degree with a focus area, students are required to take the above three core courses and advised to take five focus-area courses as shown in the program chart if all focus-area courses are offered during their span of study. Students opting for the thesis option don’t need to take additional courses. Students opting for graduate paper or comprehensive exam option are required to take one or two additional electives, respectively. Note that students are advised to follow a focus area where possible but they need not to declare one for their degree completion. Focus areas won’t appear on students’ transcript.
Mission Statement
The Master of Science in Electrical Engineering program will foster an environment that encourages independent thinking and creativity and prepares students to pursue doctoral degrees in electrical engineering or a related discipline. Graduates of the program will also establish proficiency in a concentrated field of study and develop professional attributes that include communication skills and ethics to deal with the impact of technology and engineering solutions in a global and societal context.
Program Educational Objectives
The Master of Science (MS) in Electrical Engineering Program Educational Objectives (PEO) are broad statements that describe what graduates are expected to attain within a few years of graduation. Program educational objectives are based on the needs of the program’s constituencies. The Electrical Engineering faculty, in conjunction with its constituents, has established the following program educational objectives:
PEO 1: Graduates will have specialized training in a concentrated field of study and develop professional attributes that include communication skills, and ethics to deal with the impact of technology in a global and societal context.
PEO 2: The program will foster an environment that encourages independent thinking and creativity that prepares them to pursue doctoral degrees in electrical engineering or related disciplines.
Program Learning Outcomes
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(Independent Thinking) Demonstrate the ability to work independently in developing innovative solutions in Electrical Engineering
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(Discipline Focus) Establish a proficiency in a concentrated course of study and research in a subfield of Electrical Engineering
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(Communication)Demonstrate the ability to communicate effectively in written and oral forms.
A shortage of electrical engineering talent in the job market, particularly in the GCC, means that the demand for RIT Dubai graduates remains at an all-time high. Our graduates are working in a range of roles including Project Managers, Systems Engineers, Project Engineers, and General Managers.
Core Courses EEEE-602 Random Signals and Noise EEEE-707 Engineering Analysis EEEE-709 Adv. Engineering Mathematics |
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General MSEE Choose 5 courses for the thesis option; |
MSEE with Focus Areas |
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Energy |
Control & Robotics |
Communications |
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EEEE-647 AI Exploration
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EEEE-647 AI Exploration EEEE-622 Elect. Power Trans. & Dist. EEEE-624 Advances in Power Systems EEEE-661 Modern Control Theory EEEE-789 ST - Smart Grids |
EEEE-647 AI Exploration EEEE-636 Biorobotics/Cybernetics EEEE-661 Modern Control Theory EEEE-685 Principles of Robotics EEEE-765 Optimal Control |
EEEE-647 AI Exploration EEEE-629 Antenna Theory EEEE-693 Digital Communications EEEE-797 Wireless Communications |
Electives No additional courses are required for the thesis option |
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EEEE-636 Biorobotics/Cybernetics EEEE-743 Digital Controls |
EEEE-743 Digital Controls EEEE-789 ST - Smart Grids |
EEEE-636 Biorobotics/Cybernetics EEEE-685 Principles of Robotics EEEE-789 ST - Smart Grids |
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Thesis EEEE-790 (6 Credits) Graduate Paper EEEE-792 (3 Credits) |
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Total Credits: 30 |
Total Credits: 30 |
Total Credits: 30 |
Total Credits: 30 |
Notes:
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Students are advised to follow a focus area where possible but they need not to declare one for their degree completion. Focus areas won’t appear on students’ transcript.
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The graduate paper (EEEE-792) must be completed in one semester and is graded with letter grades F- A. Students may not split the graduate paper credits over multiple semesters.
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Students must maintain a cumulative GPA of 3.0 or above at all times. A student with a cumulative GPA of less than 3.0 will be placed on probation (which may lead to suspension). University rules on probation and suspension apply.
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The minimum passing grade for graduate-level courses is “C”. Students are required to achieve a grade of “C” or above on all core courses.
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The graduate work must be completed within seven years, starting from the time the first course is applied towards the MSEE degree.
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All courses are three (3) semester credit hours.
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Graduate elective courses from the main campus can be taken with the department approval.
To graduate, students need to complete all the requirements as listed in the curriculum. Click here for the graduation policy.
Click here to download graduate catalogue for complete descriptions of each course within the program.
Smart Energy Lab (SEL)
The Robotics and Industry 4.0 LAB is designed to support and present research in the future of Industry. The main objective is to provide a platform to test and develop universal solutions to optimize the industrial processes given the technological and other industrial advances. This infrastructure is already available to the academic and research community both private and public. The Intelligent Supply Chain LAB (Located alongside the Industry 4.0 Lab) provides a test and experimentation platform to students and researchers from both industrial and academic communities to experiment and develop solutions to the integrated supply chain because of the ever-changing environment. It includes modular elements to simulate similar industrial contexts.
AI/Robotics Lab
The AI/Robotics lab fosters different use cases and projects in both AI (machine learning and deep learning) and Robotics with state-of-the-art equipment to support applications related to path planning, navigation, SLAM, Pick, and Place. Moreover, the AI/Robotics lab incorporates the AI/Robotics student club whose mission is to support students with extracurricular activities that provide them with better exposure and learning experience of skills related to AI and robotics.
Computing Security Lab
The computing security lab provides students with a PC and access to the DTLAB in order to support a wide range of courses. Examples of these courses are penetration testing, security auditing, cyber defense, network forensic, digital forensics, and many more.
Computer Networking Lab
This lab is divided into four clusters. Each cluster has two sub-clusters with three adjacent PCs. A cabinet with at least one server, firewall, two routers, and four switches is dedicated for each of the four clusters. UTP and Console cables are available for students to connect these devices into a LAN, WAN and they can connect the event to the internet to install any additional required software or tool.
Digital Transformation Lab
The digital transformation lab at RIT Dubai is funded by the TRA ICT fund and was established in 2018. The aim of this lab is in the research and development of secure and smart solutions across a number of verticals that support digitization for government, enterprise, and education.
Dr. Muhideen Amer
Professor and Chair
Dr. Wesam Almobaideen
Professor
Dr. Abdulla Ismail
Professor
Dr. Jinane Mounsef
Assistant Professor
Dr. Boutheina Tlili
Associate Professor
Eyad Shihabi Managing Director, BT |
Ghada Elkeissi Head of Professional Services, AWS |
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Taha Khalifa Regional General Manager, Middle East Intel Corp |
Dr. Ayman ElNashar VP and Head – Technology Architecture, Emirates Integrated
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Ghanim Al Falasi Senior VP – Corporate Services Dubai Silicon Oasis Authority
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Diyaa Zebian Executive Partner Archinnova |
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Dr. Mahmoud Sherif Head of Technology and IT Strategy Emirates Integrated
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Bashar Kilani Territory Executive - Middle East IBM |
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Dr. Raed Shubair Senior Advisor, Office of Undersecretary for Research Affiliate, MIT
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