Faculty of Computer Science and Engineering

Graduate

Faculty Mission

The faculty strives to produce competent professionals who have sound knowledge in the field of computing and information technology. Faculty is to produce graduates having enhanced creative thinking, problem solving skills and ability for lifelong learning in their professional careers and to develop research programs to address the evolving needs of industry, academia and society.

The graduates of the Faculty of Computer Science and Engineering shall play a productive role both in the practical and research areas of computing. The Faculty uses modern technologies to enhance the learning capabilities of the students and to provide them with a stimulating and challenging environment. Emphasis is placed on the practical applications of computer systems to the software and hardware needs of the global industry in general and the Pakistani industry in particular. The Faculty offers courses leading to Bachelor’s (BS), Master’s (MS) and Doctor of Philosophy (Ph.D.) degrees in Computer Engineering and Computer Science.

Introduction

The Faculty of Computer Science and Engineering (FCSE) is one of the five faculties at GIK Institute. FCSE offers two programs (1) Computer Science, and (2) Computer Engineering leading to Bachelor (BS), Master (MS) and Doctor of Philosophy (Ph.D.) degrees in Computer Science and Computer Engineering.

FCSE employs competent faculty members qualified to accomplish the mission and goals of the Institute. When determining acceptable qualifications of its faculty, FCSE asserts primary consideration to the terminal degree in the discipline. FCSE also considers competence, effectiveness and capacity, including, as appropriate, undergraduate and graduate degrees, related work experience in the field; professional licensure and certifications; honors, awards, and recognition; continuous documented excellence in teaching, or other demonstrated competencies and achievements that contribute to effective teaching, research, scholarship and student learning outcomes.

Graduate Programs

The Faculty of Computer Science and Engineering (FCSE) offers Master (MS) and Doctor of Philosophy (PhD) degrees in both Computer Science and Computer Engineering. Both Computer Science and Computer Engineering are multifaceted disciplines and have an assortment of applications in fields ranging from arts and humanities to business and all areas of science, engineering and technology.

Computer science is the scientific and practical approach to computation and its applications. It is the systematic study of the feasibility, structure, expression, and simulation or implementation of the algorithms and methodical procedures that underlie the acquisition, representation, processing, storage/retrieval, communication of, and access and dissemination of information. Frequently, computer science is also be considered as the study of automating algorithmic processes that scale. A computer scientist specializes in the theory of computation and the design of computational systems.

The field of Computer Science can be divided into a variety of theoretical and practical disciplines. Some fields, such as computational complexity theory which explores the fundamental properties of computational and intractable problems, are highly abstract, while fields such as computer graphics emphasize real-world visual applications. Still other fields focus on challenges in implementing computation. For example, programming language theory considers various approaches to the description of computation, while the study of computer programming itself investigates various aspects of the use of programming language and complex systems. Human–computer interaction considers the challenges in making computers and computations useful, usable, and universally accessible to humans. A graduate degree in Computer Science produces experts in one or more of these fields.

Computer engineering is a discipline that integrates fields of electrical engineering and computer science required to develop computer systems combining hardware, software or firmware. Computer engineers generally have training in electronic engineering or electrical engineering, software design, and hardware-software integration instead of only software engineering or electronic engineering. Computer engineers are involved in many hardware and software aspects of computing, from the design of individual microcontrollers, microprocessors, personal computers, and supercomputers, to circuit design. This field of engineering not only focuses on how computer systems themselves work, but also how they integrate into the larger whole.

Usual tasks involving computer engineers include writing software and firmware for embedded microcontrollers, designing VLSI chips, designing sensors or mixed signal circuit boards, and designing operating systems. Computer engineers are also suited for robotics research which relies on using digital systems to control and monitor electrical systems like motors, communications, and sensors.

Computer Engineering students are allowed to choose areas of in-depth study early on because the full breadth of knowledge is used in the design and application of computer engineering systems.

Both graduate programs require individual curricula. The graduates of these programs will be able to meet the highest standards of training for leadership in the computer science and computer engineering professions, including research, teaching, and high technology industry and R&D organizations. FCSE strongly supports the idea of using modern equipment and technologies to enhance the knowledge and learning capabilities of the students and to provide them with a stimulating and challenging environment essential for high quality education. Emphasis is laid on the innovative and practical applications of computer science and computer engineering to the software and hardware needs of the global society and industry in general and Pakistani society and industry in particular. Alongside the research activities for academic pursuits, the faculty of FCSE is actively involved in collaborative research and consultancy work with the local industry and R&D organizations and frequently invites speakers from these organizations. The summer internship of the undergraduate students in industry has added strength to such linkages.

Development of techniques that can ultimately be incorporated into a computing system to make it more efficient and available for a large class of users is a matter of principal concern to the computer scientists and engineers. Such developments need to be supported by effective usage of suitable hardware. The graduate programs of the FCSE addressed these concerns with a focus on the following research areas.

The graduate program at the Faculty of Computer Science & Engineering (FCSE) may be pursued with a specialization theme, depending upon the research interests of the available faculty, in one of the following areas:

i. Artificial Intelligence and Robotics

ii. Algorithms and Computational Theory

iii. High performance computing

iv. Machine Learning & Data Mining

v. Network Communication and Distributed Systems

vi. Signal and Image Processing and Computer Vision

vii. Software and Systems Engineering

The FCSE offers courses leading to both Master’s (MS) and Doctor of Philosophy (PhD) degrees in Computer Science and Computer Engineering.

FCSE and FEE establish an Inter-Faculty TeleCon Research Lab
 
Faculty of Computer Sciences & Engineering and Faculty of Electrical Engineering have jointly established a Telecommunications and Networking (TeleCoN) Research Lab. The Lab has been approved by the Executive Committee of SOPREST and GIK Institute. The Lab seeks to foster high-quality research focused on the design and analysis of communication systems and network architectures and protocols that are cost effective, scalable and meet the emerging needs for high-performance, high-capacity and reliable communications. The TeleCoN Research Group promotes fundamental and applied research employing cutting-edge networking, communication and signal processing techniques and technologies. General areas of interest of the TeleCoN Research Group include resource allocation, traffic management, teletraffic engineering, security, energy efficiency, cooperative communications and quality of service in Internet, wireless sensor networks, mobile ad hoc networks, vehicular ad hoc networks, cognitive radio networks, multi-user relay networks and heterogeneous cellular networks. Other activities of the Group include the organization and co-organization of seminars, workshops, lectures, trainings and invited talks to consolidate the educational and research work and to promote the objectives of the group.
 

Courses Offered:

MS degrees

The courses offered by the FCSE are categorized as core courses, faculty and inter-faculty electives. An MS student, specializing in any area, will be required to take all the core courses and a minimum of two courses from one of the areas of concentration. The remaining courses are electives and can be selected from the faculty elective courses or from those offered by other faculties.

PhD degrees

The courses to be taken up by a student will be decided by the student’s PhD Guidance Committee and approved by the Dean of Graduate School. Out of eight courses, at least five must be from the list of FCSE courses and the remainder from other faculties.

Course Work

Core Courses (for CE)

S.No. Course Code Course Name Credit Hour

1

CSE 501

Advanced Algorithms and Computational Techniques

3

2

CSE 503

Advanced Operating Systems

3

3

CSE 504

Advanced Computer Architecture

3

4

CSE 602

Probability and Stochastic Processes

3

Software Engineering Specialization Electives

S.No. Course Code Course Name Credit Hour

1

CSE 517

Semantic Web

3

2

CSE 518

Web Engineering

3

3

CSE 541

Advanced Software Engineering

3

4

CSE 542

Software Testing and Reliability

3

5

CSE 543

Advanced Software Quality Assurance

3

6

CSE 544

Advanced Human Computer Architecture

3

7

CSE 545

Software Risk Management

3

8

CSE 546

Advanced Human Computer Interaction

3

9

CSE 547

Formal Methods in Software Engineering

3

10

CSE 549

Software Process Engineering

3

11

CSE 550

Software Process Management and Improvement

3

Database Management and Data Mining

S.No. Course Code Course Name Credit Hour

1

CSE 551

Advanced Database Management Systems

3

2

CSE 552

Multimedia and Hypermedia Systems

3

3

CSE 553

Data Mining

3

4

CSE 554

Big Data Analytics

3

Digital Signal Processing

S.No. Course Code Course Name Credit Hour

1

CSE 573

Statistical Signal Processing

3

2

CSE 574

Video Signal processing

3

3

CSE 576

Speech and Audio Processing

3

Digital Image Processing and Computer Vision

S.No. Course Code Course Name Credit Hour

1

CSE532

Signal & Image Processing

3

2

CSE 533

Pattern Recognition/VR based Systems

3

3

CSE 534

Advanced Computer Graphics

3

4

CSE 535

Advance Image Processing

3

5

CSE 536

Medical Image Processing

3

6

CSE 537

Multimedia Systems

3

7

CSE 538

Computer Vision

3

8

CSE 540

Image and Video Coding

3

9

CSE 632

Machine Learning

3

10

CSE 633

Digital Image Watermarking

3

11

CSE 681

Optical Computing

3

Computer Networks and Distributed Computing

S.No. Course Code Course Name Credit Hour

1

CSE 521

Queuing Theory/Computer Networks II

3

2

CSE 522

Mobile and Wireless Networks

3

3

CSE 523

Advanced Security and Forensics

3

4

CSE 524

Multimedia Services Over IP Networks

3

5

CSE 525

Parallel and Distributed Computing

3

6

CSE 526

Cluster and Cloud Computing

3

7

CSE 527

Routing and Switching

3

8

CSE 528

High Performance Networks

3

9

CSE 529

Mobile and Pervasive Computing

3

Communications

S.No. Course Code Course Name Credit Hour

1

CSE 581

Advanced Digital Communication

3

2

CSE 582

Advanced Mobile & Wireless Communication

3

3

CSE 583

QOS in Telecommunication Networks

3

Artificial Intelligence and Scientific Computing

S.No. Course Code Course Name Credit Hour

1

CSE 561

Advanced Artificial Intelligence

3

2

CSE 562

Advance Artificial Neural Networks

3

3

CSE 563

Knowledge Engineering & Expert Systems

3

4

CSE 564

Pattern Recognition

3

5

CSE 565

Genetic Algorithms / Evolutionary Computation

3

6

CSE 566

Knowledge Management

3

7

CSE 568

Information Retrieval and Query Processing

3

8

CSE 571

Graph Theory

3

9

CSE 572

Natural Language Processing

3

10

CSE 573

Statistical Image Processing

3

11

CSE 574

Finite Element Methods

3

12

CSE 660

Advance Numerical and Simulation Techniques

3

13

CSE 661

Machine Learning and Computer Vision

3

14

CSE 671

Analysis of Stochastic Processes

3

Advance Topics

S.No. Course Code Course Name Credit Hour

1

CSE 511

Theory of Automata II

3

2

CSE 512

Compiler Construction

3

3

CSE 513

Quantum Computing

3

4

CSE 636

Advance Numerical and Simulation Techniques

3

Duration of the MS Program and semester wise workload:

The courses offered by the FCSE are categorized as core courses, faculty and inter-faculty electives. An MS student, specializing in any area, will be required to take three out of four core courses and a minimum of two courses from one of the areas of concentration. The remaining courses are elective and can be selected from the FCSE elective courses or from those offered by other faculties.

Semester 1

S.No. Code Course Title Cr. Hrs.

S. No.

Code

Course Title

Cr. Hrs.

1

CSE

Core -1

3

2

CSE

Core -2

3

3

CSE

Elective – I

3

Semester 2

S.No. Code Course Title Cr. Hrs.

S. No.

Code

Course Title

Cr. Hrs.

1

CSE

Core -3

3

2

CSE

Elective II

3

3

CSE

Elective – III

3

Semester 3

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSExx

Elective – IV

3

2

CSExx

Elective – V

3

3

CSE599

Thesis-I

3

Semester 4

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE599

Thesis-2

3

Duration of the PhD Program and semester wise workload:

The courses offered by the FCSE are categorized as core courses, faculty and inter-faculty electives. A PhD student, specializing in any area, will be required to take courses that PhD Guidance Committee decides and approved by the Dean of Graduate School. Out of eight at least five must be from the list of FCSE courses and the remaining courses may be from other faculties.

Semester 1

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Core -1

3

2

CSE

Core -2

3

3

CSE

Elective – I

3

Semester 2

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Core -3

3

2

CSE

Elective – II

3

3

CSE

Elective – III

3

Semester 3

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Elective – IV

3

2

CSE

Elective – V

3

3

CSE

Thesis-I

3

Semester 4

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-II

3

Semester 5

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-III

3

Semester 6

S.No. Code Course Title Cr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-IV

3

Course Description

Code Name Lecture Hours Lab Hours Credit Hours Pre-reqs Co-reqs
CSE501 Advance Algorithms and Computational Techniques 3 0 3 none none
CSE503 Advanced Operating System 3 0 3 none none
CSE504 Advanced Computer Architecture 3 0 3 none none
CSE511 Theory of Automata-II 3 0 3 none none
CSE512 Compiler Construction 3 0 3 none none
CSE513 Quantum Computing 3 0 3 none none
CSE514 Advance Computer Systems 3 0 3 none none
CSE518 Web Engineering 3 0 3 none none
CSE521 Queuing Theory/Computer Networks-II 3 0 3 none none
CSE525 Parallel and Distributed Computing 3 0 3 none none
CSE529 Mobile and Pervasive Computing 3 0 3 none none
CSE532 Signal and Image Processing 3 0 3 none none
CSE533 Pattern Recognition/ Virtual Reality Based Systems 3 0 3 none none
CSE535 Advanced Image Processing 3 0 3 none none
CSE538 Computer Vision 3 0 3 none none
CSE539 Robotic Vision 3 0 3 none none
CSE541 Advanced Software Engineering 3 0 3 none none
CSE542 Software Testing and Reliability 3 0 3 none none
CSE543 Advanced Software Quality Assurance 3 0 3 none none
CSE544 Advanced Human Computer Interaction 3 0 3 none none
CSE551 Advanced Database Management Systems 3 0 3 none none
CSE552 Multimedia and Hypermedia Systems 3 0 3 none none
CSE554 Big Data Analytics 3 0 3 none none
CSE561 Advanced Artificial Intelligence 3 0 3 none none
CSE562 Advanced Artificial Neural Networks 3 0 3 none none
CSE563 Knowledge Engineering & Expert Systems 3 0 3 none none
CSE564 Pattern Recognition 3 0 3 none none
CSE571 Graph Theory 3 0 3 none none
CSE573 Statistical Signal/Image Processing 3 0 3 none none
CSE574 Finite Element Methods 3 0 3 none none
CSE581 Advanced Digital Communication/Quantum Computing 3 0 3 none none
CSE590 Special Topics in Computer Science 3 0 3 none none
CSE591 Special Topics in Computer Engineering 3 0 3 none none
CSE598 Master Project Report 0 0 6 none none
CSE599 Master Thesis 0 0 9 none none
CSE602 Probability and Stochastic Processes 3 0 3 none none
CSE632 Machine Learning 3 0 3 none none
CSE633 Digital Image Watermarking 3 0 3 none none
CSE636 Advanced Numerical and Simulation Techniques 3 0 3 none none
CSE637 Data Authentication Techniques 3 0 3 none none
CSE638 Analysis of Stochastic Processes 3 0 3 none none
CSE661 Machine Learning and Computer Vision 3 0 3 none none
CSE671 Analysis of Stochastic Processes 3 0 3 none none
CSE681 Optical Computing 3 0 3 none none
CSE699 Ph.D. Dissertation 0 0 18 none none

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