Air University Kamra Campus

Department of Electrical & Avionics Engineering Introduction Head Of Department Message Programs Offered Mission Statement Faculty Program Educational Objectives (PEOs) Program Learning Outcomes (PLOs) Curriculum Salient Features of Department Laboratories

Department of Electrical & Avionics Engineering

Dr. Bilal Ashraf

Lecturer

Ext: +92-57-9153-220

Email: [email protected]

Dr. Bilal Ashraf

Lecturer

Dr. Bilal Ashraf is a Lecturer in the Department of Electrical & Avionics Engineering at Air University Aerospace & Aviation Campus, Kamra. He has been associated with the campus since 2020, after serving as Visiting Faculty at Air University Islamabad in 2019. His academic background is in Electrical Engineering, with teaching and research experience spanning undergraduate and graduate-level engineering education.

He completed his Ph.D. in Electrical Engineering from Air University Islamabad. His doctoral research focused on cardiac arrhythmia classification for imbalanced and noisy ECG data using deep feature embeddings. His broader research interests include artificial intelligence, deep learning, biomedical signal processing, biomedical image processing, computer vision, explainable AI, and control systems.

Dr. Bilal Ashraf has supervised multiple undergraduate final-year projects, including applied engineering and funded research-oriented projects in areas such as IoT, industrial automation, artificial intelligence, computer vision, assistive technologies, biomedical systems, and intelligent control. He has also contributed to MS-level research supervision as a co-supervisor and internal member. His technical expertise includes Python, MATLAB/Simulink, TensorFlow, Keras, and PyTorch for deep learning, signal processing, system modeling, and intelligent engineering applications.

In addition to teaching and research, he contributes to academic quality assurance and curriculum development. He serves as Convener of the Outcome-Based Education Committee and as a member of the Curriculum Review Committee for the Bachelor of Electrical Engineering program.

Ph.D. in Electrical Engineering Air University Islamabad Master of Science in Electrical Engineering University of Engineering and Technology, Taxila Bachelor of Electrical Engineering Air University Islamabad

Journal Publications:

B. Ashraf, H. Ali, M. A. Khan, and F. R. Albogamy, “EffNet: An efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments,” Biomedical Physics & Engineering Express, vol. 11, no. 2, Art. no. 025041, 2025, doi: 10.1088/2057-1976/adb58a. M. A. Khan, D.-E.-Z. Baig, H. Ali, B. Ashraf, S. Khan, A. Wadood, and T. Kamal, “Efficient system identification of a two-wheeled robot (TWR) using feed-forward neural networks,” Electronics, vol. 11, no. 21, Art. no. 3584, 2022, doi: 10.3390/electronics11213584. M. A. Khan, M. A. Khan, H. Ali, B. Ashraf, S. Khan, D.-E.-Z. Baig, A. Wadood, and T. Khurshaid, “Output power prediction of a photovoltaic module through artificial neural network,” IEEE Access, vol. 10, pp. 116160–116166, 2022, doi: 10.1109/ACCESS.2022.3216384. M. A. Khan, D.-E.-Z. Baig, B. Ashraf, H. Ali, J. Rashid, and J. Kim, “Dynamic modeling of a nonlinear two-wheeled robot using data-driven approach,” Processes, vol. 10, no. 3, Art. no. 524, 2022, doi: 10.3390/pr10030524.

Conferences Publications:

M. A. Khan, A. Wadood, B. Ashraf, and M. A. Khan, “Genetic algorithm optimization of economic load dispatch of IEEE-6 units power system with valve-point loading effects,” presented at the 4th International Conference on Sustainable Energy Technologies (ICSET-22), 2022.

Artificial Intelligence and Deep Learning Biomedical Signal Processing Biomedical Image Processing ECG Signal Classification and Cardiac Arrhythmia Detection Explainable Artificial Intelligence Computer Vision Control Systems System Modeling and System Identification Optimization Techniques Power System Optimization

IoT-Enhanced Variable Frequency Drive (VFD) with AI-Based Predictive Maintenance IIoT-Based Smart Mini Factory Computer Vision-Based Assistance System for Visually Impaired People Brain-Controlled Wheelchair Using a Brain–Computer Interface