Bio
Muhammad Javaid Aslam is a Ph.D. researcher in Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST). His work focuses on smart power networks, the impact of electric vehicles on power systems, and AI-based energy optimization for sustainable cities.
His research integrates machine learning, optimization, electric-vehicle charging infrastructure, vehicle-to-grid coordination, renewable generation, and demand-side energy management. Current interests include forecasting-based EV charging dispatch, battery-preserving scheduling, solar-aware charging, peak-load reduction, and resilience of distributed energy systems.
Before joining HKUST, he served at the University of Gujrat in Pakistan as Lecturer and Laboratory Engineer in Electrical Engineering, teaching and supervising work in power electronics, digital logic design, electromagnetic field theory, electrical machines, power systems, energy auditing, and EV battery charging optimization.
Academic & Professional Appointments
Lecturer, Electrical Engineering
University of Gujrat, Pakistan · Mar 2022 – present, currently on leave for Ph.D.
Taught Power Electronics, Digital Logic Design, and Electromagnetic Field Theory; supervised final-year projects in EV battery charging optimization and power electronics; served on curriculum, assessment, FYP, admission, and outreach committees.
Laboratory Engineer, Electrical Engineering
University of Gujrat, Pakistan · Feb 2014 – Feb 2022
Supported courses and laboratories in power electronics, electrical machines, power generation, power systems, communication systems, electronics, network analysis, engineering management, and energy auditing.
Laboratory Engineer, Electrical
Sharif College of Engineering & Technology, Lahore · Dec 2012 – Jan 2014
Designed and established the Instrumentation & Control Laboratory and supported instrumentation, measurements, analog electronics, and workshop practice.
Electrical Engineer
Creative Electronics Pvt. Ltd., Lahore · Feb 2009 – Nov 2012
Led meter testing and maintenance activities, conducted IEC/WAPDA-standard tests, trained officials on meter software and tariff settings, and supervised 3-phase meter production and configuration.
Professional Education
Ph.D., Electronic & Computer Engineering
Hong Kong University of Science and Technology · Sep 2024 – present
Focus: smart power networks, EV impacts on power systems, and AI-based energy optimisation.
M.Phil. / M.Sc., Energy Engineering
University of Engineering & Technology Lahore · 2013 – 2019
Thesis: Short Term Load Forecasting using Regression and Artificial Neural Networks.
B.Sc., Electronics & Communication Engineering
University of Engineering & Technology Lahore · 2004 – 2008
Research Interests
- Machine learning and artificial intelligence for optimization
- Vehicle-to-grid decision systems and distributed energy storage management
- EV charging scheduling, solar-aware dispatch, and battery-preserving optimization
- Short-term load forecasting under outage-prone and data-limited conditions
- Smart power networks, energy management, microgrids, and sustainable cities
Selected Publications
Journal Articles
J1A. Naveed, M. Wasif, J. Irshad, J. Aslam, S. Manzoor, T. Kausar, and Y. Lu, “Saliency-Based Semantic Weeds Detection and Classification Using UAV Multispectral Imaging,” IEEE Access, 2023. DOI: 10.1109/ACCESS.2023.3242604
J2J. Aslam, M. Kamran, A. Arif, M. Wasif, J. Irshad, and I. Hussain, “Short Term Load Forecasting under Extensive Power Outages Using Domestic Energy Meter Load Profile: A Case Study,” Journal of Engineering Research, 2022. DOI: 10.36909/jer.ICEPE.19559
J3A. Rauf, J. Irshad, Z. Mehmood, M. Wasif, J. Aslam, and S. Miran, “A Review of Learning-Based SLAM Approaches of Autonomous Unmanned Vehicles,” Journal of Engineering Research, 2022.
Conference & Proceedings Papers
C1J. Aslam et al., “AI-Driven Vehicle-to-Grid Decision System for Distributed Energy Storage Management and Grid Resilience,” Proc. IEEE EESAT, 2026. DOI: 10.1109/EESAT65054.2026.11404104
C2J. Aslam et al., “Outage-Prone Neural Networks Analysis for Short-Term Electrical Demand Forecasting,” Proc. IEEE ISGT-Asia, 2025. DOI: 10.1109/ISGTAsia63446.2025.11431413
C3M. Ali, J. C. Vasquez, J. M. Guerrero, Y. Guan, J. De La Cruz, and M. J. Aslam, “Ad-hoc Microgrids Planning for Rural Communities under Natural Disasters,” Proc. IEEE ICEPECC, 2023.
C4J. Aslam, W. Latif, M. Wasif, I. Hussain, and S. Javaid, “Comparison of Regression and Neural Network Model for Short Term Load Forecasting: A Case Study,” Engineering Proceedings, MDPI, 2021.
Funded Projects
EV Battery Charging Cycle Optimisation using Machine Learning
NGIRI-IGNITE, Government of Pakistan · 2023–2024
Information System for Consumed Electricity with On-Demand Billing Notifier
Pakistan Engineering Council · 2023–2024
Peer Review & Professional Service
- IEEE Access — 75 reviews
- Energy Conversion and Management, Elsevier — 30 reviews
- Energy Conversion and Management: X, Elsevier — 10 reviews
- Energy Efficiency, Springer — 2 reviews
- Microsoft CMT conference management — 3 reviews
- PEC Journal of Engineering, Pakistan Engineering Council — 2 reviews
Technical Skills
Simulation & Engineering Tools
MATLAB/Simulink, Cadence Virtuoso, OrCAD PSpice, LTspice, ETAP, Proteus, Multisim, OriginPro
Programming & Documentation
Python, MATLAB/Octave, Verilog HDL, LaTeX, Microsoft Office Suite
Platforms
Linux/Ubuntu, Google Workspace, MATLAB Academy