The Ph.D. program in Computer Science offers an in-depth exploration of advanced topics in computing, research methodologies, and theoretical frameworks. Students engage in cutting-edge research under the mentorship of renowned faculty, contributing to the forefront of computer science knowledge. With a focus on innovation and problem-solving, graduates emerge as experts equipped to tackle complex challenges in areas such as artificial intelligence, cybersecurity, data science, and beyond, shaping the future of technology through groundbreaking research and scholarship.
The career path for individuals with a Ph.D. in Computer Science is multifaceted and offers opportunities across various sectors. Some common career paths include:
Academia, Industry Research, Technology Leadership, Government and Public Sector, Entrepreneurship, Data Science and Analytics, Consulting and Non-Traditional Roles
A Ph.D. in Computer Science opens doors to a wide range of career opportunities, allowing graduates to contribute significantly to research, innovation, and problem-solving in various sectors.
Entry Requirement for Ph.D. Computer Science
Duration of PhD Program:
Minimum 3 Years
Maximum 8 Years (As per the Institute’s Policy)
The curriculum of the Program:
Program Credit Hours
Course Work: 18 credit hours
Research Work and Research Thesis: 30 credit hours
|
Code |
Course Title |
Credit Hours |
Labs |
Total |
1 |
COMP-XXX |
Compute Science Elective Course – I |
2NG |
|
|
2 |
COMP-XXX |
Compute Science Elective Course – II |
3 |
|
3 |
3 |
COMP-XXX |
Compute Science Elective Course – III |
3 |
|
3 |
|
|
Total Credit Hours |
9 |
|
9 |
|
Code |
Course Title |
Credit Hours |
Labs |
Total |
1 |
COMP-XXX |
Compute Science Elective Course – IV |
3 |
|
3 |
2 |
COMP-XXX |
Compute Science Elective Course – V |
3 |
|
3 |
3 |
COMP-XX |
Compute Science Elective Course – VI |
3 |
|
3 |
|
|
Total Credit Hours |
9 |
|
9 |
|
Code |
Course Title |
Credit Hours |
Labs |
Total |
1 |
COMP-899 |
Thesis |
30 |
|
30 |
2 |
|
Total Credit Hours |
30 |
|
30 |
|
Grand Total Credit Hours: 48 |
||||
|
|
Specialized Core Courses: |
|
|
|
|
|
The Ph.D. programs can offer all courses with course codes starting with COMP-8## or COMP-9##. Courses relevant to the specialization of the degree offered by another department can also be taken with the approval of the supervisor. Some of the already approved courses are given below. |
|
|
|
|
|
Elective Courses |
|
|
|
1 |
COMP-852 |
Wireless Packet Data Networks and Protocols |
3 |
|
3 |
2 |
COMP-853 |
Mobile Adhoc Networks (MANETs) |
3 |
|
3 |
3 |
COMP-854 |
Advanced Wireless Networks |
3 |
|
3 |
4 |
COMP-855 |
Network Functions Virtualization (NFVs) |
3 |
|
3 |
5 |
COMP-874 |
Fault Tolerant Systems |
3 |
|
3 |
6 |
COMP-892 |
Advanced Network Security |
3 |
|
3 |
7 |
COMP-856 |
Networks Analytics |
3 |
|
3 |
8 |
COMP-898 |
Advanced Ethical Hacking |
3 |
|
3 |
9 |
COMP 857 |
Advanced Network Modeling and Simulation |
3 |
|
3 |
10 |
COMP-858 |
Advanced Network Programming |
3 |
|
3 |
11 |
COMP-830 |
Tools and Techniques for Data Science |
3 |
|
3 |
12 |
COMP-831 |
Knowledge Engineering |
3 |
|
3 |
13 |
COMP-832 |
Advanced Information Retrieval |
3 |
|
3 |
14 |
COMP-833 |
Advanced Big Data Analytics |
3 |
|
3 |
15 |
COMP-834 |
Advanced Data Visualization |
3 |
|
3 |
16 |
COMP-840 |
Statistical and Mathematical Methods for Data Analysis |
3 |
|
3 |
17 |
COMP-841 |
Machine Learning for Data Science |
3 |
|
3 |
18 |
COMP-842 |
Advanced Machine Learning |
3 |
|
3 |
19 |
COMP-843 |
Advanced Artificial Neural Network |
3 |
|
3 |
20 |
COMP-844 |
Advanced Deep learning |
3 |
|
3 |
21 |
COMP-845 |
Advanced Natural Language Processing |
3 |
|
3 |
22 |
COMP-846 |
Advanced Expert and Recommender Systems |
3 |
|
3 |
23 |
COMP-847 |
Advanced Digital Image Processing |
3 |
|
3 |
24 |
COMP-848 |
Advanced Knowledge Representation and Reasoning |
3 |
|
3 |
25 |
COMP-849 |
Computational Intelligence and IoT |
3 |
|
3 |
26 |
COMP-940 |
Computer Vision and Pattern Identification |
3 |
|
3 |
27 |
COMP-941 |
AI for Biomedical Engineering |
3 |
|
3 |
28 |
COMP-942 |
AI in Smart Energy Systems |
3 |
|
3 |
29 |
COMP-943 |
Distributed Data Processing and Machine Learning |
3 |
|
3 |