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

Program Structure

The PhD Computer Science Program is a 3-8 years degree program consisting of 18 credit hours of course work and 30 credit hours of research work. The department offers PhD degree with the research emphasis on following research areas:

1. Data Science
2. Artificial Intelligence
3. Information Systems
4. Networking and Communication
5. Machine Learning and Computer Vision
6. Human Computer Interaction

Second Semester

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

Courses List

CSC-7001 Modeling of Web Information Systems

Web modeling concepts; Modeling the Webapplications for requirements engineering; Contentmodelling; Navigation modeling (Hypertext, Accessstructure); Modeling the presentation for the enduser; Model driven development and model drivenarchitecture; Evolution of the Web, Web 1.0 (visualWeb), Web 2.0 (Social Web), and Semantic Web (theWeb of metadata); Hypertext patterns; Persistence ofHT patterns; O&M of Web applications.

CSC-7002 Data Warehousing

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

CSC-7003 Peer-To-Peer Systems

Overview of P2P Systems and brief history; Taxonomyof P2P Networks/Systems and Analysis of popularP2P 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 inpeer-to-peer systems; Social, Legal and Privacy aspectsof P2P Systems.

CSC-7004 Multimedia Retrieval Techniques

Multimedia content and motivations for multimediaretrieval; Issues of multimedia Retrieval. Multimediaretrieval models; Content-based image retrieval;Content-based video retrieval; Content-basedaudio retrieval: audio representations, audio featureextraction; 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 ofschemes and metadata communities; Functionsand Types of metadata; Metadata Structure andCharacteristics: Semantics, syntax, and structure;Metadata creation process models; Interoperability;Metadata Integration and Architecture: WarwickFramework; Resource Description Framework; OpenArchives Initiative; Encoding Standards (MarkupLanguages): Introduction and history of markup;Metadata use of markup languages; Document TypeDefinitions (DTD); Structural metadata Data ControlStandards: Resource Identifiers; Data Registries;Controlled vocabularies; Name authority control(ISAAR and FRANAR); A-Core; Encoded ArchivalDescription (EAD), Text Encoding Initiative (TEI);Metadata Evaluation: User needs; Quality controlissues; Evaluation methods; Educational Metadata:Instructional Management Systems (IMS); LearningObject Metadata (LOM); Gateway to EducationalMaterials (GEM); Government Information LocatorService (GILS); Visual Resources Metadata: Categoriesfor the Description of Works of Art (CDWA); VisualResources Association (VRA) Core; ComputerInterchange of Museum Information (CIMI)

CSC-7006 Information Privacy and AccessControl

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

CSC-7007 Ubiquitous Information Interaction

Information Interaction; Seminal ideas of ubiquitouscomputing; Tangibility and Embodiment; Socialcomputing; Privacy; Critical and cultural perspectives;Mobility and Spatiality; Mobile Technology in the MessyNow; Infrastructure; Seams, seamlessness, seamfulness; Evaluating Interaction of Ubicomp systems

CSC-7008 Human Information

InteractionOverview of the course and a brief history; Typesand structures of information resources; Types andstructures of vocabularies; Information retrieval &Interaction in information retrievalSearch engines, Digital libraries; Search techniquesand effectiveness; Advanced searchingWeb search and the invisible web; Information seeking30 National Textile Universitybehavior; User modeling ; Mediation between searchintermediaries and users; Evaluation of search sourcesand results; Result Presentation to users; Keeping up:sources for life-time learning.

CSC-7009 Information Architecture

Introduction and Overview of the course. Process ofWeb development; Information behavior & the web.Content design and organization systems; Copyrightissues. Labeling systems; Writing for the Web. Navigationdesign; Search systems. Page design; Multimedia.Web usability evaluation & testing. Accessibilityfor users with disabilities. Global audiences; Webstandards & policies. Weblogs, Intranets, Websites formobile devices; Web design software; Web ContentManagement Systems. Metadata; Search engines.

CSC-7010 Collaborative Data Mining

Overview of the course and a brief history; Overviewof Distributed Database systems; Importance andusage of collaboration; Web Data Resources; A briefintroduction to overlay networks; Remote Collaboration;Collaborative Data Mining Guidelines; Parallel DataMining; Grid-based Data Mining; Collaborative miningover social networks; Collaborative mining in P2PNetworks; Collaborative data mining case studies.

CSC-7011 Communication Networks

Overview of the course & research activities in computernetworks; 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 P2PNetworks; Multimedia Information & Networking;Network Measurement.

CSC-7012 Advances in Next Generation Networks

Next Generation Internet/Networks: “Convergence toIP”; Network Technologies and Architectures; Qualityof Service; Multimedia protocols; Policy routing;Future Internet; Network traffic optimization; NextGeneration Internet and broadband deployment;Advances in wireless mobile networks; Advances insensor networks; Management of Next GenerationNetworks.

CSC-7013 P2P-based Information retrieval

Overview of the Information Retrieval Systems;Multimedia & its characteristics; P2P Systems & itscharacteristics; Content searching/locating in P2Psystems; 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 informationretrieval.

CSC-7014 Advanced Software Architecture

Re-use in architectures: Software product lines,evaluation and validation of product lines, productline testing, re-use in product lines; Service orientedarchitectures (SOAs): SOA concepts, risks andchallenges, quality attributes and SOAs, evaluatingand testing SOAs; Architectural evaluation: Methodsfor architectural analysis, Comparison of methods;Architectural evolution and reconstruction: Models ofsoftware evolution, analysis and metrics for evolution,Techniques and tools for architecture reconstruction;Architectures in dynamic environments: Modeling andanalyzing dynamic software architectures; Self healingarchitectures: The need for self-healing, approachesfor self healing.

CSC-7015 Artificial Intelligence

This course considers ideas and techniques fromArtificial Intelligence. It first introduces a range ofsearch algorithms that are used throughout AI. It thenexamines applications and techniques of AI, includingrule-based systems for embodying human expertise,algorithms for planning and problem solving, naturallanguage processing, methods for machine learning,and neural nets and other computation intelligencetechniques.

CSC-7016 Advanced topics in Machine Learning

Introduction: Overview of machine learning, Machinelearning applications and examples; Reinforcementlearning: Elements of reinforcement learning,Model based learning, Temporal difference learning,Generalization; Genetic Algorithms: Genetic operators,fitness function, Hypothesis space search, Geneticprogramming; Support Vector Machines: Optimalseparating hyperplane, softmargin hyperplane, kernelfunctions, SVMs for regression; Combining learners:Voting, Bagging, Boosting; Assessing and ComparingClassification Algorithms: Cross-validation andresampling, Measuring error, Assessing performance,Comparing multiple classification algorithms.

CSC-7017 Evolutionary Computation

Evolutionary Computation can be considered as a subfieldof Artificial Intelligence. Evolutionary algorithmsare inspired in the principles of natural selection andgenetics. This course explores how principles fromtheories of evolution and natural selection can beused to construct machines that exhibit nontrivialbehavior. In particular, the course covers techniquesfrom genetic algorithms, genetic programming, andlearning classifier systems for developing softwareagents capable of solving problems as individuals andas members of a larger community of agents.

CSC-7018 Research Seminar

This course offers a substantial introduction relevantto doctoral work in student’s research area. The courseprovides directed and supervised investigation ofselected topics. Each week Research papers related tothe topic will be discussed, and presented in a seminarformat. This course progresses as a series of seminars,each presenting a different paper(s). It preparesstudents to review studies of other researchers in thefield, and allows them to become more knowledgeableabout methods appropriate to their dissertationresearch.

• 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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