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
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
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
Designed and established the Instrumentation & Control Laboratory and supported instrumentation, measurements, analog electronics, and workshop practice.
Electrical Engineer
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
Focus: smart power networks, EV impacts on power systems, and AI-based energy optimisation.
M.Phil. / M.Sc., Energy Engineering
Thesis: Short Term Load Forecasting using Regression and Artificial Neural Networks.
B.Sc., Electronics & Communication Engineering
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. DOI: 10.36909/jer.ICEPE.19549
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. DOI: 10.1109/ICEPECC57281.2023.10209509
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. DOI: 10.3390/engproc2021012029
Funded Projects
EV Battery Charging Cycle Optimisation using Machine Learning
Information System for Consumed Electricity with On-Demand Billing Notifier
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
Volunteer Service
Convener, College Outreach Committee
Coordinated outreach activities and supported engagement between the college, students, and external stakeholders.
Chair, Blood Donor Society
Led volunteer coordination and student service activities for blood donation and community support initiatives.
Evaluator, National Projects & Poster Competition
Served as evaluator for student innovation, engineering projects, and poster presentations at a national competition.
Project Evaluator, National Events
Reviewed and evaluated engineering student projects in academic and professional events.
Training & Certifications
Professional Training
Workshop on Urban Metabolism Modeling with AI
Reliability of Battery Energy Storage Systems Using AI
Use of Generative Artificial Intelligence in Higher Education
Outcome-Based Education for Engineering
Cadence EDA Tools: Genus, Innovus, Tempus, Virtuoso
Selected Online Courses & Certifications
Machine Learning
X-Series: Circuits & Electronics
Managing Machine Learning Projects with Google Cloud
Industrial IoT on Google Cloud Platform
MATLAB Onramp, Machine Learning Onramp, and Deep Learning Onramp
Introduction to Power Electronics
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