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

          Semester-II

          Semesters III-VIII

List of Core  Courses

List of Elective  Courses

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

Courses Contents

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-7001: 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-7002: 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-7003: 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-7004: 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-7005: 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-7006: 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-7007: 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-7008: 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-7009: 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-7010: 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-7011: 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-7012: 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-7013: 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-7014: 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-7015: 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-7016: 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-7017: 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-7018: 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.

• MS / M.Phil Computer Science / IT / Software Engineering or equivalent with minimum 3.00/4.00 or 3.50/5.00 CGPA in semester system, 60% marks in annual system.
• The applicant must pass NTU-GAT (Subject) test with minimum 70 % score as per HEC.
• It is mandatory to pass the interview to compete on merit.
• Applicant must not be already registered as a student in any other academic program in Pakistan or abroad.
• Applicants having MS without thesis are not eligible to apply.

Admission Criteria

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

NOTE: 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.

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