RESEARCH @ FES – ACTIVE & PROPOSED
Dr. Asad Mahmood
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.
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.
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.
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 (email@example.com)
Prof. Dr. Muhammad Hassan Sayyad
Prof. Sayyad heads the Organic Electronics and Photonics group that works on
Contact: Prof. Dr. Muhammad Hassan Sayyad, FES (firstname.lastname@example.org )
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.
For further details please visit the group’s homepage
Contact: Prof. Dr. Jameel-Un Nabi (email@example.com)
Dr. Muhammad Tayyab
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.firstname.lastname@example.org)
Engr. Dr. Muhammad Usman
Solid-state lighting is being adopted globally to conserve energy and reduce CO2 emissions. Light-emitting diodes and laser diodes are solid-state lighting sources. The group’s research work focuses on the design and analysis of efficient light-emitting diodes and laser diodes from infrared (IR) to ultraviolet (UV) emissions. The group lead is the pioneer of the subject research area in Pakistan. Applications of solid-state lighting include lighting, horticulture, poultry, light therapy etc. Moreover, the group is also working on energy economics and energy-savings for the needs of Pakistan.
Contact: Engr. Dr. Muhammad Usman, FES (email@example.com)
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
Contact: Dr. Muhammad Zahir Iqbal, FES (firstname.lastname@example.org )
Dr. Naveed R. Butt
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.
Estimation of time-varying fundamental frequency is an important problem in many real-life applications, e.g. analysis of electroencephalogram (EEG) seizure signals. Instantaneous fundamental frequency of such signals is usually estimated by first windowing a signal and then applying methods such as non-linear least square. However, this approach is approach is based on an assumption that a given signal is stationary within an observation time. Research under this topic will focus on efficiently handling the non-stationarity.
Contact: Dr. Naveed R. Butt, FES (email@example.com)
Dr. Tahseen Amin Khan Qasuria
Semiconductor and Microelectronics lie at core of electronics engineering, finding its application in modern electronics, communication systems, defense industry, automobile, medical diagnostic equipment, biomedical electronic and space industry. Semiconductor and Microelectronics is not only limited to the above-mentioned areas, but it opens up interdisciplinary opportunities in the area of photonics, materials, chemicals, nanotechnology, and micro-electro-mechanical systems MEMS. Semiconductor and Microelectronics is also a key to a sound understanding of nanotechnology, a developing technology which has potential to improve our quality of life in diverse ways, such as faster electronics, huge memory/storage devices. Semiconductor technology provides the state of art solutions to the photovoltaic technology for the economical production and storage of electricity. Organic semiconductor is another area which produces OLEDs, flexible displays, and a variety of multifunctional sensors. Organic Semiconductor students can explore new horizons for the betterment of humanity and can upraise the standard of living by providing economical and efficient solutions to the problems.
Contact: Dr. Tahseen Qasuria, FES (firstname.lastname@example.org)
Dr. Sakander Hayat
Dr. Sakander mainly works in the areas of discrete mathematics and its applications to different scientific disciplines. Currently, he is engaged in areas of graph theory and combinatorics. He focuses on both of
theoretical and applicative perspectives of these areas.
For theoretical part of his research, he is currently focusing on following directions:
1. Employing tools from linear algebra and group theory to characterize graphs with few distinct eigenvalues corresponding to the adjacency, the distance, the Laplacians, and other graph-theoretic matrices.
2. Using tools from linear algebra and spectral graph theory such as interlacing, Perron-Frobenius theorem, equitable partitions, Sylvester’s inertia law, and divisors to study main and plain eigenvalues of graphs.
3. Studying extremal properties of graph-theoretic descriptors by employing tools from set theory and theory of inequalities.
4. Solving open problems related to the domination number and the metric dimension of graphs.
For applied part of his research, he is mainly engaged on working on the following directions:
1. Addressing degeneracy of graph-theoretic topological descriptors by employing graph signal processing and spectral graph theory.
2. Studying topological properties of interconnected networks and artificial neural networks by means of graph-theoretic parameters such as the clique number, chromatic number, independence number, maximal and perfect matchings, matching ratio, and minimal dominating sets and the domination number etc.
3. Applications of novel irregularity descriptors in QSAR modelling and their mathematical properties.
Contact: Dr. Sakander Hayat, FES Sakander.email@example.com
Dr. Usman Habib
Future mobile networks are considering the millimeter-wave (mmW) spectrum for wider bandwidth and low congestion. However, the generation and transmission of mmW for a large number of remote antenna units, and compatibility with optical fiber-based fronthaul network is still a challenge. Related topics of interest include
Contact: Dr. Usman Habib, FES (firstname.lastname@example.org)
Dr. Fahd Sikandar Khan
Dr. Fahd is currently working on a host of exciting and cutting edge interdisciplinary projects focused around sustainable ENERGY in line with the United Nation’s (UN) Sustainable Development Goal (SDG) number 7.
Major topics of research interest include
Green Energy Development – Hydrogen Economy (in collaboration with University of Exeter, UK)
Blockchain-based Applications (in collaboration with various Foreign Industrial Partners and US-based Pak Launch)
Contact: Dr. Fahd S. Khan, FES (email@example.com)