|Research Group Name||Members|
|Communication and Networks||
Dr. Muhammad Haneef (Head)
Engr Sajjad Karim
Engr. M. Ali
Engr. Fawad Khan
Engr. Muhammad Azam
|Control and Power Engineering||
Engr. Abdur Rehman (Head)
Engr. Zain Ul Islam
Engr. Bilal Mushtaq
Engr. Muhammad Azam
Engr. Hana Amin Khan
|Signal Processing and Pattern Recognition||
Dr. Nabeel Ali Khan (Head)
Engr. M Ali
Engr. Sajad Karim
Engr. Adnan A Khan
In many real-life situations, it is important to automatically classify a given signal based on its characteristics, e.g. detection of seizures in EEG signals. This problem of signal classification is usually solved by a combination of signal processing techniques and machine learning algorithms. The signal analysis methods like time-frequency analysis and wavelet transform are used in the first stage to extract features that can better separate one class of signals from others. The second stage employs machine learning/pattern recognition techniques for classifying the extracted features to achieve the final decision. This interdisciplinary research group focuses combines signal processing expertise from the Electrical Engineering department and machine learning expertise from the computer science department to develop and efficiently implement algorithms for the classification of real-life signals such as biomedical signals. The focus research areas are:
1) Design of advanced signal analysis techniques for the analysis of non-stationary signals.
2) Extraction of features from joint time-frequency representations.
3) Application and enhancement of existing machine learning algorithms for the classification of non-stationary signals.
4) Real-time implementation of algorithms on hardware and software platforms such as GPUs/FPGAs/DSPs.
Control & Power Engineering group focuses on the application of control theory in network control systems and interconnected power systems. Research of this group spans through a variety of areas including but not limited to nonlinear control systems, quantization, multi-agent systems, fault-tolerant control, renewable energy systems, energy conversion and conservation, microgrids, flight control systems, cyber-physical systems, and robotics.