Faculty Of Engineering Sciences

Graduate

WELCOME TO THE GRADUATE PROGRAM!!

The Faculty of Engineering Sciences (FES) offers graduate courses and facilitates research leading to MS and Ph.D. degrees in the emerging fields of engineering science and technology in order to produce effective practicing engineers and researchers. The program is focused to cope with the urging demands of the new millennium industrial needs of the country. Alongside excellence in teaching, FES aims to become a center of excellence in research and development in the various fields of engineering sciences and technology. The Graduate Program at GIK Institute is ensured to be of international standards. The faculty, equipment, laboratories and library facilities provide easy access for the students to the latest corpus of knowledge in their fields of specialization.

KEY BENEFITS OF JOINING GIK

  • Highly Reputed Institute in Engineering Sciences and Technology
  • Quality Research and Research Facilities
  • Highly Qualified Faculty
  • Fully Residential Campus, with a Clean and Safe Environment and Easy Access to Labs Round the Clock.
  • Scholarships & Assistantships Available [Click Here to Learn More]

GRADUATE PROGRAMS AT FES

We offer MS and PhD degree programs in the following exciting fields:

Group A: Applied Mathematics

Group B: Applied Physics

Group C: (1) Digital System Engineering  (2) Photonics Engineering

To learn more about the courses offered and degree requirements, Click Here.

HOW TO APPLY [Admission & Scholarships]

  • For Application Procedure, Admission Requirements, Eligibility and Assessment Criteria, Click Here
  • To Learn about applying for scholarships/assistantships, Click Here

RESEARCH @ FES – ACTIVE & PROPOSED

Note: Listed below are sample topics. For a complete list of research activities at FES see Faculty Profiles , Research Groups, and Lab Facilities.

Dr. Asad Mahmood

  • Intrinsic dimensionality estimation in Hyperspectral Images

Hyperspectral Images (HSI) form an important component of modern remote sensing. These images consist of a number of spectral bands, unlike the commonly known RGB images which consist of only three spectral bands, and hence provide useful information about the characteristics of the materials which are being imaged. HSI are capture via satellites, airplanes as well as UAVs, and are used in a number of applications such as land mapping, vegetation and water monitoring, surveillance, target detection, cancer detection etc. One of the most important information extracted from a digital hyperspectral image is the estimation of the number of end-members/materials present in an image, which is also known as the intrinsic dimensionality estimation problem. In this project the student will work on novel signal processing techniques to determine the intrinsic dimensionality in the hyperspectral image.

  • Deep Learning for Hyperspectral Image Analysis

Hyperspectral Images (HSI) form an important component of modern remote sensing. These images consist of a number of spectral bands, unlike the commonly known RGB images which consist of only three spectral bands, and hence provide useful information about the characteristics of the materials which are being imaged. HSI are capture via satellites, airplanes as well as UAVs, and are used in a number of applications such as land mapping, vegetation and water monitoring, surveillance, target detection, cancer detection etc. Deep learning has recently become the preferred method for inferring useful information from a real hyperspectral image. In this project, the student will apply recent developments from the deep learning community for important information extraction tasks in hyperspectral images, such as classification, unmixing and intrinsic dimensionality estimation.

  • Machine learning for physical layer wireless communication algorithms

Wireless communication has revolutionized our way of communications and many of the everyday communication technologies belong to this genre, e.g. WiFi, 4G, etc. One of the latest trends in the research area of wireless communications is the application of machine learning techniques for the various signal processing tasks at the physical layer such as channel estimation, adaptive modulation and coding etc. In this project, the student will make use of new developments from the machine learning community and apply them for optimization tasks at the physical layer of wireless communications.

  • Reconstruction algorithms for Compressed Sensing

Compressed Sensing is a relatively new area in the area of signal processing where the sparsity of the underlying signal is exploited in order to come up with better algorithms for signal estimation. Reconstruction algorithms aim to recover the original signal from the compressed signal in which the number of available samples are less than the Nyquist limit. Different algorithms have been devised for the reconstruction purposes, such as Bayesian algorithms, iterative thresholding algorithms etc. In this project different reconstruction algorithms will be analyzed for reconstruction purposes and improvements will be devised for their usage in a particular application e.g. hyperspectral images.

Contact: Dr. Asad Mehmood, FES  (asad.mahmood@giki.edu.pk)

Prof. Dr. Muhammad Hassan Sayyad

Prof. Sayyad heads the Organic Electronics and Photonics group that works on

  • Green Photonics, Printed Photonics
  • Computational design and synthesis of organic semiconductors, quantum dots, nanoparticles, and nanocomposites
  • Characterization of various types of optical and electronic properties
  • Computational modeling and fabrication of  organic electronic and photonic devices, such as, junction diodes, transistors, memories, sensors, next-generation solar cells, batteries, supercapacitors
  • Design and development of next-generation solar cell technology based solar panels

Contact: Prof. Dr. Muhammad Hassan Sayyad, FES (sayyad@giki.edu.pk  )

Prof. Dr. Jameel-Un Nabi

Study of our Universe is by no means an easy task. The complex astrophysical phenomena involved makes the problem very challenging and indeed knowhow of basic sciences, engineering, modeling and simulation is the minimal requirement for a better understanding of our Universe. The nucleosynthesis problem (r-, s-, p- and rp-processes), evolution phases of stars and supernova explosions are few astrophysical phenomena that require microscopic calculation of weak interaction rates at high temperatures (of the order of billions of kelvin) and high densities (of the order of 1011 g/cm3). Besides we also need calculation of other input data before we can run the mega codes on supercomputers to model these phenomena.

Our group is part of a world-wide effort to microscopically calculate the inputs for these simulation and modeling codes. The group is mainly concerned with the calculation of nuclear data. The results are then given to collaborators running the simulation codes. Various nuclear models (e.g. QRPA, shell model) are employed to calculate the inputs. Numerical techniques, computer programming and understanding of the physical phenomena are the basic requirements in our group. The group also uses other models like Potential Model and R-Matrix to calculate astrophysical S-factors and proton capture rates.

Experimental work is done in collaboration with other experimental groups. This include renewable energy technologies.

Research Topics:

  • Calculation of β-decay half-lives for exotic nuclei.
  • Calculation of allowed Gamow-Teller, Fermi and forbidden charge-changing transitions.
  • Calculation of weak-interaction mediated rates in stellar conditions.
  • Calculation of nuclear partition functions, nuclear level densities and nuclear abundances.
  • r-, s-, p- and rp-process calculations.
  • Double beta decay calculations (two-neutrino and neutrinoless modes)
  • Use of pn-QRPA, Shell model, Pyatov method, Schematic Model and other nuclear models to microscopically calculate the nuclear data.
  • Astrophysical S-factor and proton capture rates.
  • Mass abundance computations
  • Fuel cells, PVs, semitransparent thermoelectric and semitransparent photo-thermoelectric cells

For further details please visit the group’s homepage

Contact: Prof. Dr. Jameel-Un Nabi (jameel@giki.edu.pk)

Dr. Muhammad Tayyab

  • A key approach to anomalous diffusion by deterministic and stochastic processes

In real-world problems, diffusion of matter and heat is a widely well-known phenomenon.. Therefore, in the realm of normal and anomalous diffusion, deterministic processes play a vital role in the investigation of microscopic properties of non-trivial systems (stochastic) and leave many unanswered questions. Such properties are invisible but yet to investigate by simple toy models.

The proposed research project is focused on the development of deterministic dynamics to investigate the elusive properties of stochastic processes such as Levy-Lorentz gas, Levy walk, and CTRW.

Contact: Dr. M. Tayyab, FES (Muhammad.tayyab@giki.edu.pk)

Dr. Muhammad Usman

  • Design and analysis of light-emitting didoes

Light-emitting diodes are the energy-efficient lighting source that have been replacing traditional light sources globally. The proposed research work will focus on the design and analysis of light-emitting diodes. The group lead is the pioneer of this research area in Pakistan. Applications include lighting, horticulture, poultry, and light therapy.

Contact: Engr. Dr. Muhammad Usman, FES (m.usman@giki.edu.pk)

Dr. Muhammad Zahir Iqbal

Dr. Zahir is currently working on synthesis, characterization and applications of the nanomaterials of various metal oxides, phosphates, sulfides and conducting polymers for supercapacitors, batteries and electrochemical sensors. Major topics of research interest include

  • Energy storage devices
  • Photovoltaic
  • Batteries
  • Optoelectronic devices
  • Spintronic
  • Biosensors
  • Field effect transistors
  • Raman spectroscopy

Contact: Dr. Muhammad Zahir Iqbal, FES (zahir@giki.edu.pk )

Dr. Naveed R. Butt

  • Classification of Raman Spectra Collected from Dangerous Materials

Raman spectroscopy is a powerful non-contact technique that uses a laser to probe the vibrational energy levels of molecules in a substance. The vibration Information provided by a Raman spectrum is very specific for the chemical composition of the molecules. The spectrum can therefore provide unique Signature for identification of vapor traces from various materials. The proposed research work will focus on developing adaptive and intelligent classification schemes for Raman spectra collected at a stand-off distance from dangerous materials. Applications include safety and security.

Other topics

  • Robust Signal Processing for Spectroscopy Applications
  • Sparse Methods for Hyperspectral Imaging
  • Beamforming for Multipitch Estimation and Remote Sensing Applications

Contact: Dr. Naveed R. Butt, FES (naveed.butt@giki.edu.pk)

Dr. Tahseen Qasuria

  • Design and Fabrication of the Organic Semiconductor Devices
  • Design and Fabrication of the Solar Cells
  • Design and Fabrication of the Photovoltaic System
  • Design and Fabrication of the Sensors
  • Design and Fabrication of the Sensors for the Telemetry System Applications

Contact: Dr. Tahseen Qasuria, FES (qasuria@giki.edu.pk)

 

Meet Our Graduates

  SHAMS UL ARIFEEN (Applied Mathematics )

  Ph.D. Student

 Research Title: Numerical Solution of Differential equations via Finite Element  Method

The Division’s research in this area mostly focuses on developing efficient and stable numerical methods for approximating solutions to differential equations that arise in a wide range of engineering and science applications. For decades now the scientific computing and numerical analysis group have been at the forefront in the development of efficient and robust method like Redial Basis function, Haar wavelet, Locus and Fibonacci Polynomial Approximation, Finite Element Method, Finite difference and Finite Volume Method for solution of differential equations.

SADAF SHAHEEN (Aplied Mathematics )

Ph.D. Student

Research Title:Developing a modified method to solve different kind of Partial Differential Equations using  Matlab