Doctoral Programs

PhD Computer Science

  • To promote high achievement in theoretical and practical problems within the field of computer science and to address the burgeoning education demands for graduates and professionals with advanced Computer Science education.
  • To offer students a solid background in core areas and exposure to cutting-edge research in computer science.
  • To improve the qualifications, skills and expertise of teachers and researchers in order to provide highly competent professionals to various public and private universities.

PhD graduates should be able to:

  1. Identify research questions in emerging computing sciences and independently conduct competitive solutions in comparison with state of the art solutions.
  2. Demonstrate the ability of scientifically communicate technical information of their related discipline
  3. Research and critique computing literature and utilize it for proposing a solution
  4. Demonstrate the advance and practical concepts of computing

 Semester-I

Code

Subject Title

Credit Hours

CSC-XXXX

Core-1

3

CSC-XXXX

Core-2

3

CSE-XXXX

Elective-I

3

 

Total

9

          Semester-II

Code

Subject Title

Credit Hours

CSE-XXXX

Elective-II

3

CSE-XXXX

Elective-III

3

CSE-XXXX

Elective-IV

3

 

Total

9

          Semesters III-VIII

 Code

Subject Title

Credit Hours

 CSC-XXXX

Research Work / Thesis

30

 

(This list is not exhaustive, and new courses can be added to this category at any time depending upon the availability of the instructor)

List of Core Courses

 

Sr. No.

Code

Course Title

Credit Hours

1

CSC-XXXX

Advanced Research Methods

3

2

CSC-XXXX

Formal Specification and Verification

3

3

CSC-XXXX

Mathematics for Computer Science

3

4

CSC-XXXX

Research Seminars

3

List of Elective Courses

 

Sr. No.

Code

Course Title

Credit Hours

1

CSE-700X

Modeling of Web Information Systems

3

2

CSE-700X

Data Warehousing

3

3

CSE-700X

Peer-To-Peer Systems

3

4

CSE-700X

Multimedia Retrieval Techniques

3

5

CSE-700X

Metadata for Information Resources

3

6

CSE-700X

Information Privacy and Access Control

3

7

CSE-700X

Ubiquitous Information Interaction

3

8

CSE-700X

Human Information Interaction

3

9

CSE-700X

Information Architecture

3

10

CSE-70XX

Collaborative Data Mining

3

11

CSE-70XX

Communication Networks

3

12

CSE-70XX

Advances in Next-Generation Networks

3

13

CSE-70XX

P2P-based Information retrieval

3

14

CSE-70XX

Advanced Software Architecture

3

15

CSE-70XX

Artificial Intelligence

3

16

CSE-70XX

Advanced topics in Machine Learning

3

17

CSE-70XX

Evolutionary Computation

3

Course Specifications

CSC-XXXX: Formal Verification and Specification

Problem in Software Development, Formal Methods for the problems, Three levels of formal method, Design Process Uses, Automated Proof, Formal Languages, Validation, Precedence, Set operators, Power sets, Subjects and predicate, Symbolization Convention, Negative Quantifiers, Binary Relations, Reflexivity, Restricted Kind of Relation, Function Application, Sequences, Sequence Filtering, Theory of Equality, Set Difference, Domain Restriction Operator 

CSC-XXXX: Advanced Research Methods

Overview of the course and a brief history; Introduction and overview of the subject. The nature of Computer Science (CS) research; what is research? Literature searches, information gathering, Reading and understanding research papers, Technical writing, referencing, bibliographies, Presentation skills, written and oral. Choosing or proposing a project. Project planning, tools, and techniques for planning. Project conduct, time management, risk management, teamwork. Commercial and economic considerations in IT research and the IT industry. Review legal, ethical, social, and professional (LSEP) issues, including data protection and standards.

 

CSC-700X: Modeling of Web Information Systems

Web modeling concepts; Modeling the Web applications for requirements engineering; Content modeling; Navigation modeling (Hypertext, Access structure); Modeling the presentation for the end-user; Model-driven development and model-driven architecture; Evolution of the Web, Web 1.0 (visual Web), Web 2.0 (Social Web), and Semantic Web (the Web of metadata); Hypertext patterns; Persistence of HT patterns; O&M of Web applications.

CSC-700X: Data Warehousing

Overview of the course and a brief history; Data Warehouse Architecture; Extract Transform Load; Data Cleansing Algorithms; Hot and Cold Data; Data Warehouse support for OLAP and Data Mining; Active Data warehousing; Semantic Data warehousing; Oracle solution Teradata solution; Case Studies.

CSC-700X: Peer-To-Peer Systems

Overview of P2P Systems and brief history; Taxonomy of P2P Networks/Systems and Analysis of popular P2P Systems; Analysis of unstructured P2P Systems; Analysis of structured P2P Systems; Search Efficiency; P2P-based content delivery; Security and Reliability; Replication in peer-to-peer systems; Anonymity in peer-to-peer systems; Social, Legal and Privacy aspects of P2P Systems.

CSC-700X: Multimedia Retrieval Techniques

Multimedia content and motivations for multimedia retrieval; Issues of multimedia Retrieval. Multimedia retrieval models; Content-based image retrieval; Content-based video retrieval; Content-based audio retrieval: audio representations, audio feature extraction; Query modalities and similarity measures; Analysis of existing multimedia retrieval systems, retrieval evaluation criteria, relevance feedback; current trends in Multimedia Retrieval.

CSC-700X: Metadata for Information Resources

Overview of the course and Metadata; History of schemes and metadata communities;  Functions and Types of metadata; Metadata Structure and Characteristics: Semantics,  syntax,  and structure; Metadata creation process models; Interoperability; Metadata Integration and Architecture: Warwick Framework; Resource Description Framework; Open Archives Initiative; Encoding Standards (Markup Languages): Introduction and history of markup; Metadata use of markup languages; Document Type Definitions (DTD); Structural metadata Data Control Standards: Resource Identifiers; Data Registries; Controlled vocabularies; Name authority  control (ISAAR and FRANAR); A-Core; Encoded Archival Description (EAD), Text Encoding Initiative (TEI); Metadata Evaluation: User needs; Quality control issues; Evaluation methods; Educational Metadata: Instructional Management Systems (IMS); Learning Object Metadata (LOM); Gateway to Educational Materials (GEM); Government Information Locator Service (GILS); Visual Resources Metadata: Categories for the Description of Works of Art (CDWA); Visual Resources Association (VRA) Core; Computer Interchange of Museum Information (CIMI).

CSC-700X: Information Privacy and Access Control

Privacy, Privacy policies; Privacy enforcement; Adaptive privacy management; Access control mechanisms; Different access control models such as Mandatory, Discretionary, Role-Based and Activity-Based; Access control matrix model; Harrison-Russo-Ullman model and undecidability of security; Confidentiality models such as Bell-LaPadula; Integrity models such as Biba and Clark-Wilson; Conflict of interest models such as the Chinese Wall.

CSC-700X: Ubiquitous Information Interaction

Information Interaction; Seminal ideas of ubiquitous computing; Tangibility and Embodiment; Social computing; Privacy; Critical and cultural perspectives; Mobility and Spatiality; Mobile Technology in the Messy Now; Infrastructure; Seams, seamlessness, seamfulness; Evaluating Interaction of Ubicomp systems.

CSC-700X: Human Information Interaction

Overview of the course and a brief history; Types and structures of information resources; Types and structures of vocabularies; Information retrieval & Interaction in information retrieval Search engines, Digital libraries; Search techniques and effectiveness; Advanced searching Web search and the invisible web; Information seeking behavior; User modeling; Mediation between search intermediaries and users; Evaluation of search sources and results; Result Presentation to users; Keeping up: sources for life-time learning.

CSC-700X: Information Architecture

Introduction and Overview of the course. Process of Web development; Information behavior & the Web. Content design and organization systems; Copyright issues labeling systems; Writing for the Web. Navigation design; Search systems. Page design; Multimedia. Web usability evaluation & testing. Accessibility for users with disabilities. Global audiences; Web standards & policies. Weblogs, Intranets, Websites for mobile devices; Web design software; Web Content Management Systems. Metadata; Search engines.

CSC-70XX: Collaborative Data Mining

Overview of the course and a brief history; Overview of   Distributed Database systems; Importance and usage of collaboration; Web Data Resources; A brief introduction to overlay networks; Remote Collaboration; Collaborative Data Mining Guidelines; Parallel Data Mining; Grid-based Data Mining; Collaborative mining over social networks; Collaborative mining in P2P Networks; Collaborative data mining case studies.

CSC-70XX: Communication Networks

Overview of the course & research activities in computer networks; Communication Networks & Services; Overview of network simulations; Layered architecture; Congestion Control and Traffic Management; Wireless, Mobility, and Cross-layer concepts; Switching & Routing; Quality of Service (QoS); Multicast; Peer-to-Peer (P2P) and Overlay Networks; Content Distribution in P2P Networks; Multimedia Information & Networking; Network Measurement.

CSC-70XX: Advances in Next-Generation Networks

Next Generation Internet/Networks: Convergence to IP; Network Technologies and Architectures; Quality of Service; Multimedia protocols; Policy routing; Future Internet; Network traffic optimization; Next Generation Internet and broadband deployment; Advances in wireless mobile networks; Advances in sensor networks; Management of Next Generation Networks.

CSC-70XX: P2P-based Information retrieval

Overview of the Information Retrieval Systems; Multimedia & its characteristics; P2P Systems & its characteristics; Content searching/locating in P2P systems; Emerging coding standards for information; Architecture of P2P-based information retrieval; Privacy & security issues in P2P-based information retrieval; Current research trends in P2P-based information retrieval.

CSC-70XX: Advanced Software Architecture

Re-use in architectures: Software product lines, evaluation, and validation of product lines,  product line testing, re-use in product lines; Service-oriented architectures (SOAs): SOA concepts, risks and challenges, quality attributes and SOAs, evaluating and testing SOAs; Architectural evaluation:  Methods for architectural analysis, Comparison of methods; Architectural evolution and reconstruction: Models of software evolution, analysis, and metrics for evolution, Techniques, and tools for architecture reconstruction; Architectures in dynamic environments: Modeling and analyzing dynamic software architectures; Self-healing architectures: The need for self-healing, approaches for self-healing.

CSC-70XX: Artificial Intelligence

This course considers ideas and techniques from Artificial Intelligence. It first introduces a range of search algorithms that are used throughout AI. It then examines applications and techniques of AI, including rule-based systems for embodying human expertise, algorithms for planning and problem solving, natural language processing, methods for machine learning, and neural nets, and other computation intelligence techniques.

CSC-70XX: Advanced Topics in Machine Learning

Introduction Overview of machine learning, Machine learning applications, and examples, Reinforcement learning, Elements of reinforcement learning, Model-based learning, Temporal difference learning, Generalization, Genetic Algorithms, Genetic operators, fitness function, Hypothesis space search, Genetic programming, Support Vector Machines, Optimal separating hyperplane, soft margin hyperplane, kernel functions, SVMs for regression, Combining learners, Voting, Bagging, Boosting, Assessing and Comparing Classification Algorithms, Cross-validation, and resampling, Measuring error, Assessing performance, Comparing multiple classification algorithms.

CSC-70XX: Evolutionary Computation

Evolutionary Computation can be considered as a sub-field of Artificial Intelligence. Evolutionary algorithms are inspired by the principles of natural selection and genetics. This course explores how principles from theories of evolution and natural selection can be used to construct machines that exhibit nontrivial behavior. In particular, the course covers techniques from genetic algorithms, genetic programming, and learning classifier systems for developing software agents capable of solving problems as individuals and as members of a larger community of agents.

CSC-70XX: Research Seminar

This course offers a substantial introduction relevant to doctoral work in student’s research areas. The course provides directed and supervised the investigation of selected topics. Each week Research papers related to the topic will be discussed and presented in a seminar format. This course progresses as a series of seminars, each presenting a different paper(s). It prepares students to review studies of other researchers in the field and allows them to become more knowledgeable about methods appropriate to their dissertation research.

  1. MS /M.Phil Computer Science /IT/Software Engineering or equivalent degree with minimum 3.00/4.00 or 3.50/5.00 CGPA in semester system/60% marks in annual system.
  2. Applicants having terminal degrees as prescribed in condition no. 01, are required to qualify NTU-GAT (General) test with minimum 60% score while applicants having different terminal degree are required to qualify NTU-GAT (Subject) test additionally with minimum 50% score as per HEC.
  3. Applicant having MS or equivalent degree without thesis is not eligible to apply.
  4. It is mandatory to pass interview in order to compete on merit.
  5. Applicant must not be already registered as a student in any other academic program in Pakistan or abroad.
  6. Result waiting applicants may apply for admission, however their merit will be finalized only on submission of final MS/M.Phil or equivalent official transcript or degree.
  7. Relevant Admission Committee will determine relevancy of terminal degree and decide deficiency course/s (if any) at the time of admission interview, the detail of which will be provided to the student in his/her admission letter/email.
  8. Deficiency course/s will be treated as non-credit and qualifying course/s for which student will also pay extra dues as per fee policy. Those course/s will neither be mentioned in student’s final transcript nor will be included for calculation of CGPA. However, the student may obtain his/her a separate transcript for completion of deficiency course/s.

Merit Criteria

The admission merit list will be prepared according to the following criteria:

 MS/Equivalent  60% weightage
 B.Sc/BE/Equivalent  20% weightage
 Interview result  10% weightage
 Publication/relevant experience  10% weightage (05% + 05%)

Fee Structure of Postgraduate Programs for Admission 2023

Programs

Total One Time Dues at Admission (Rupees)

Tuition Fee (1st Semester) (Rupees)

Total Other Charges (Per Semester) (Rupees)

Total 1st Semester Dues (Rupees)

Ph.D. Computer Science

           32,400

            33,600

             8,000

74,000


Detail of One Time Admission Dues and Other Charges

Particulars 

Rupees 

Admission Fee (Once at admission) 

25,000 

Certificate Verification Fee (Once at admision) 

2,000 

University Security (Refundable) 

5,000 

Red Crescent Donation (Once at admision) 

100 

University Card Fee (Once at admision) 

300

Library Fee (Per Semester)

3,000

Examination Fee (Per Semester)

3,000

Medical Fee (Per Semester)

2,000

Student Activity Fund (Per Semester)

2,000

Endowment Fund (Per Semester)

1,000

Degree Fee (Once in the Last Semester)

5,000

 

Note:

 (i) Tuition Fee will increase @ 2.5% Per Annum in Subsequent Years.

(ii) The Security Deposit is against breakage and/or any other damage caused by the students.

(iii) The Security Deposit is refundable within two year after the completion of degree or leaving the

the University without completion or expulsion from the University. After Two years all the unclaimed

securities will be forfeited.

(iv) If any student fails to submit semester dues till sixth week from the commencement of semester

then the student's admission will be cancelled. Student may sit in mid exam after the payment of

re-admission fee of Rs.15,000/- along with semester dues.

 

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