Faculty of Computer Science and Engineering

Graduate Programs FCSE

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

FCSE GRADUATE STUDENTS

Engr. Jalees Ur Rahman

Ph.D. Scholar (Computer Engineering)

Supervisors: Dr. Muhammad Hanif and Prof. Dr. Zahid Halim

Research Area: Convolutional Neural Networks, Medical Image Processing

Research Topic: Complex-Valued Deep Neural Networks for the       Activation Detection in 3D Multichannel Data
Jalees Ur Rahman has completed his BS from COMSATS University Abbottabad and MS with distinction from Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology. Before starting Ph.D., he worked as a Data Analyst of Cancer Genomics at the National Center for Big Data and Cloud Computing (NCBC) affiliated with Lahore University of Management Sciences (LUMS). He joined GIK Institute as a Ph.D. scholar in 2020 as Graduate Assistant (Level-4) on full scholarship. He has prepared a team of young and talented programmers from the first semester, which secured the first position in the International Collegiate Programming Contest (ICPC) Asia West two consecutive times. His research interests include Neural Networks Optimization, Multidimensional and Complex-Valued CNNs, Computer Vision, Medical Image Processing, and freelancing.

Mr. Usman Haider

Ph.D. Scholar (Computer Engineering)

 Supervisor: Dr. Muhammad Hanif

Research Area: Neural Network Optimization, Sparse representation,     

Research Topic: Optimization of deep learning models for resource constraint systems

Usman Haider has completed his BS with distinction from FAST NUCES and MS with high distinction from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology. Before starting Ph.D., he was affiliated with the Lahore University of Management Sciences (LUMS) and worked as a Lecturer at the National University of Science and Technology (NUST). He joined GIK Institute as a Ph.D. scholar in 2021 as Graduate Assistant on full scholarship. His research interests include Neural Networks Optimization, Sparse representation, and Computer vision. He has authored ten research publications so far. He has worked on the pruning of Convolution Neural Networks. Currently, his research is focused on reducing the computational training cost of CNN through data and network optimization using sparse representation and quantization.

Ms. Sania Akhtar

Ms. Sania Akhtar

Ph.D. Computer Sciences

Advisor: Dr. Muhammad Hanif 

Research Area: Medical Image Processing, Machine Learning, Deep Learning, Data Analytics

Research Topic: Urine Sediment Detection and Classification Using Deep Learning 

Sania Akhtar completed her undergraduate and graduate degrees with distinction from COMSATS Islamabad and gained experience as a research assistant in the healthcare domain using machine learning techniques at SZABIST Islamabad. She is currently a graduate assistant on full scholarship at GIK, working on a project in collaboration with Kutahya Dumlupinar University in Turkey on urine sediment detection, classification, and analysis to aid in the diagnosis of kidney and renal infections. During her first year of Ph.D., she was invited by Prof. Hamidi Melih to Visit the Department of Engineering and Electronics at Kutahya Dumlupinar University in Turkey to collaborate on a project at the Neurotechnology Education Application and Research Center. The project focused on developing “Deep Learning for Microscopic Urine Sediment Classification” techniques. The primary objective of the visit was to gain experience from their research team and to participate in multiple meetings with their researchers, engineers, and medical professionals to verify the labeled data.  

Mr. Usama Arshad

Ph.D. Computer Science

Supervisor: Prof. Dr. Zahid Halim

Research Area: Blockchain, ITS, Digital twins, 5G

When it comes to acquiring a Doctoral degree, an excellent research atmosphere and university are crucial. Ghulam Ishaq Khan Institute (GIKI) provides a fantastic learning and growing atmosphere. I came on board on a full scholarship as a Graduate Assistant (GA4) and Ph.D. Computer Science candidate. Before GIKI, I completed MS Computer Science from COMSATS University Islamabad (CUI) & B.ed from Allama Iqbal Open University (AIOU). I believe anyone can reach their goals and do wonders with a little consistent effort and faith.

 

Course Work

Core Courses (for CE)

S.No.Course CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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 CodeCourse NameCredit 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. 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.CodeCourse TitleCr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-II

3

Semester 5

S.No.CodeCourse TitleCr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-III

3

Semester 6

S.No.CodeCourse TitleCr. Hrs.

S.No.

Code

Course Title

Cr. Hrs.

1

CSE

Thesis-IV

3

Course Description

CodeNameLecture HoursLab HoursCredit HoursPre-reqsCo-reqs
CSE501Advance Algorithms and Computational Techniques303nonenone
CSE503Advanced Operating System303nonenone
CSE504Advanced Computer Architecture303nonenone
CSE511Theory of Automata-II303nonenone
CSE512Compiler Construction303nonenone
CSE513Quantum Computing303nonenone
CSE514Advance Computer Systems303nonenone
CSE518Web Engineering303nonenone
CSE521Queuing Theory/Computer Networks-II303nonenone
CSE525Parallel and Distributed Computing303nonenone
CSE529Mobile and Pervasive Computing303nonenone
CSE532Signal and Image Processing303nonenone
CSE533Pattern Recognition/ Virtual Reality Based Systems303nonenone
CSE535Advanced Image Processing303nonenone
CSE538Computer Vision303nonenone
CSE539Robotic Vision303nonenone
CSE541Advanced Software Engineering303nonenone
CSE542Software Testing and Reliability303nonenone
CSE543Advanced Software Quality Assurance303nonenone
CSE544Advanced Human Computer Interaction303nonenone
CSE551Advanced Database Management Systems303nonenone
CSE552Multimedia and Hypermedia Systems303nonenone
CSE554Big Data Analytics303nonenone
CSE561Advanced Artificial Intelligence303nonenone
CSE562Advanced Artificial Neural Networks303nonenone
CSE563Knowledge Engineering & Expert Systems303nonenone
CSE564Pattern Recognition303nonenone
CSE571Graph Theory303nonenone
CSE573Statistical Signal/Image Processing303nonenone
CSE574Finite Element Methods303nonenone
CSE581Advanced Digital Communication/Quantum Computing303nonenone
CSE590Special Topics in Computer Science303nonenone
CSE591Special Topics in Computer Engineering303nonenone
CSE598Master Project Report006nonenone
CSE599Master Thesis009nonenone
CSE602Probability and Stochastic Processes303nonenone
CSE632Machine Learning303nonenone
CSE633Digital Image Watermarking303nonenone
CSE636Advanced Numerical and Simulation Techniques303nonenone
CSE637Data Authentication Techniques303nonenone
CSE638Analysis of Stochastic Processes303nonenone
CSE661Machine Learning and Computer Vision303nonenone
CSE671Analysis of Stochastic Processes303nonenone
CSE681Optical Computing303nonenone
CSE699Ph.D. Dissertation0018nonenone
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