Introduction:
The Doctor of Philosophy (PhD) program in Electrical Engineering prepares graduates for industrial or academic research in the fields of Communication, Embedded System, Control, and Power System Engineering. PhD Electrical Engineering program focuses on producing skilled researchers who can contribute by creation of new knowledge and propose solutions to challenges faced by the practitioners and researchers of the discipline.
Program Mission:
The PhD in Electrical Engineering strives to provide an environment, which is conducive to create new knowledge, for independent or collaborative research, and to produce highly skilled professional and academicians.
Program Educational Objectives
The objectives of PhD (Electrical Engineering) program are
1. To equip scholars with necessary knowledge relevant tools and techniques to make significant contribution in the field of study by conducting quality research independently or in collaboration.
2. To prepare scholars to effectively disseminate result in the form of written and oral presentation
3. To produce skilled professionals who can take up the challenges associated with the advancement of science and technology in industry or in academia.
Program Learning Outcomes
PhD scholars who successfully complete their PhD in Electrical Engineering will be able to:
PLO 1: Perform advance research that is grounded in theory, practice and further extends the existing research in the field
PLO 2: Produce quality research that have a positive impact toward the welfare and betterment of society
PLO 3: Communicate effectively both in oral and written formats to a diverse audience.
PLO 4: Collaborate with the peers in the domain of Electrical Engineering to integrate diverse perspectives
Program structure:
The PhD program consists of 18 credit hours of course work and 36 credit hours of research work. Coursework should be completed in the first two semesters. After successful completion of coursework, a PhD scholar is required to appear in the comprehensive examination. After passing comprehensive examination PhD scholar can register in the research phase by registering THS 900 PhD Thesis course. The first milestone in research phase is to prepare and submit a research Proposal under the guidance of a supervisor. The scholar appears before a panel of examiners to defend the research proposal. After successful defense, the scholar needs to carry out his/her research and complete total 36 credits of research. The scholar will present the research finding in the form of a written thesis, which shall be evaluated as per HEC and BU rules. For further details about rules governing PhD programs refer to PhD Rules Handbook.
Semester wise breakdown of the program is as follows.
SEMESTER I | ||
---|---|---|
Course code | Subject | Credits |
ESC 801 | Research Methods in PhD Studies |
3 |
Elective- I | 3 | |
Elective- II | 3 | |
Total Credits for 1st Semester | 9 |
SEMESTER II | ||
---|---|---|
Course code | Subject | Credits |
Elective- III | 3 | |
Elective- IV | 3 | |
Elective- V | 3 | |
Total Credits for 2nd Semester | 9 |
SEMESTER III | ||
---|---|---|
Course code | Subject | Credits |
Comprehensive exam | 0 | |
THS-900 | PHD Thesis | 9 |
Total Credits for 3rd Semester | 9 |
SEMESTER IV | ||
---|---|---|
Course code | Subject | Credits |
THS 900 | PHD Thesis | 9 |
Total Credits for 4th Semester | 9 |
SEMESTER V | ||
---|---|---|
Course code | Subject | Credits |
THS-900 | PHD Thesis | 9 |
Total Credits for 5th Semester | 9 |
SEMESTER VI | ||
---|---|---|
Course code | Subject | Credits |
THS-900 | PHD Thesis | 9 |
Total Credits for 6th Semester | 9 | |
Total credit for PHD program | 54 |
Core Courses
Student shall register at least 3 courses from the list of Electrical Engineering courses. EE courses offered in MS programs at Bahria University with course code 7XX shall be considered as part of Electrical Engineering courses for PhD (EE). Student can take 700+ courses from MS CS/EE/SE/Data Science and IS programs. Supervisor/Advisory committee will decide about the relevance of such courses for each scholar.
S# | Course Code | Title of Course | Cr. Hrs. |
---|---|---|---|
1 | EEN 827 | Modern Control Theory | 3 |
2 | EEN 828 | Advanced Nonlinear Control Systems |
3 |
3 | EEP 801 | Power Management in Wired and Wireless communications Systems |
3 |
4 | EEP 802 | Advanced Low Power System Design |
3 |
5 | EEP 803 | Advanced Power System Deregulation |
3 |
6 | EET 706 | Advanced Obtical Fibre Networks | 3 |
7 | EEN 829 | Design and Applications of Real Time DSP System |
3 |
8 | EET 830 | Emerging Trend in Cognitive Cooperative Networks |
3 |
9 | EEN 830 | Dynamic Systems Modeling & Simulation |
3 |
10 | EET 832 | Advance topics in Network Security |
3 |
11 | EET 833 | Smart Antennas | 3 |
12 | EET 827 | Advanced Wireless Communication Systems |
3 |
13 | EEP 804 | Advanced Power System Stability and Dynamics |
3 |
14 | EET 834 | Emerging Trend in Optical Fiber Networks |
3 |
15 | EEP 805 | Artificial Intelligence Techniques in Power Systems Design |
3 |
16 | EET 835 | Advance Topics in 5G and Beyond Communications |
3 |
17 | EEN 831 | Statistical Signal Processing |
3 |
18 | CEN 807 | Distributed Systems Architecture and Design |
3 |
19 | CEN 808 | Advanced Techniques in System Modeling and Simulation |
3 |
20 | CEN 821 | Microprocessor System Optimization and customization |
3 |
21 | CEN 840 | Advanced Embedded System Design |
3 |
22 | CEN 842 | Digital Systems Integration and Design |
3 |
23 | CEN 845 | Image Analysis and Pattern Recognition |
3 |
24 | CEN 852 | Modern Approaches in VLSI System Design |
3 |
25 | CEN 853 | Real-Time Systems Engineering & Design |
3 |
26 | CEN 855 | Advanced Parallel Processing Computer Systems |
3 |
27 | DSC 807 | Advanced Deep Learning |
3 |
28 | CSC 819 | Research Trends in Machine Learning |
3 |
29 | CSC 851 | Advanced Pattern Recognition |
3 |
30 | CSC 864 | Advanced Computer Vision |
3 |
31 | CSC 881 | Advanced Cloud Computing |
3 |
32 | SEN 862 | Emerging Trends in Big Data Analytics |
3 |
33 | SEN 819 | Advanced Neural Networks & Fuzzy Logic |
3 |
34 | EET 829 | Optimization Techniques |
3 |
35 | EEN 832 | Fuzzy Logic and Neural Network Based Intelligent control systems |
3 |
36 | EEN 833 | Advanced Computer vision for Robotics |
3 |
37 | EEN 834 | Human-Robot Interaction |
3 |
38 | EEN 835 | Medical Devices & Robotics |
3 |
39 | EET 836 | AI for Future Communication Systems |
3 |
40 | EET 837 | Advanced Data Communication Systems |
3 |
41 | EEP 806 | Modern Trends in Power system Analysis |
3 |
42 | EEP 807 | Modern Power System Protection |
3 |
43 | CEN 820 | High Performance Computer Architecture |
3 |
44 | CEN 841 | ASIC Design Methodology |
3 |
45 | CEN 854 | MOS VLSI Circuit Design | 3 |
46 | DSC 800 | Advanced Data Analytics |
3 |
47 | CSC 800 | Advanced AI Networking |
3 |
48 | SEN 809 | Internet of Things: Design and Applications |
3 |
49 | SEN 808 | Computer and Cybersecurity |
3 |
*It is mandatory to study ESC 701 Research Methodology, if the scholar has not studied this or equivalent course in MS program.
Allied Engineering Courses
Students can study maximum two allied/interdisciplinary courses during their PhD
(EE) program.
The choice of allied courses is not limited to the following list and based on PhD Supervisor’s recommendation requisite PhD course(s) from SE, CE and CS department can be registered.
61 | ESC 705 | Critical Review of Literature | 3 |
62 | GSC 701 | Logic and Research | 3 |
63 | CSC 704 | Advanced Cryptography | 3 |
64 | CSC 711 | Advanced Artificial Intelligence | 3 |
65 | GSC 700 | Advanced Engineering Mathematics | 3 |
66 | CEN 708 | Advanced System Modelling and Simulation | 3 |
67 | SEN 754 | Bio Medical Image Analysis | 3 |
68 | CSC 751 | Pattern Recognition | 3 |
69 | CSC 764 | Computer Vision | 3 |
70 | SEN 745 | Data Ware Housing and Mining | 3 |
71 | SEN 751 | Human Aspects in Software Engineering | 3 |
72 | SEN 754 | Advanced Web Computing System and Application | 3 |
Research Themes of Electrical Engineering
The EE program provides the graduates with the broad as well as in-depth technical education necessary for productive employment in the public or private sector. It aims at development of understanding of advanced issues important for current and future needs of the region. Quality research aims to encompass a broad area covering advanced digital and analogue electronics, communication, signal processing, multimedia, computer vision, advanced controls for robotics and microelectronics/nano-electronics.
The potential research themes / areas are as follows:
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