Dr. Naveed Arshad is presently Associate Professor and Director of the National Center in Big Data and Cloud Computing (NCBC) at Lahore University of Management Sciences. He is also the founder of Energy Informatics Group (EIG) and Co-Director of LUMS Energy Institute.
His research interests include energy and climate informatics; short-, medium- and long-term forecasting of energy demand, renewable energy generation forecasting for wind and solar resources, demand side management in electric transportation, agricultural, residential, and industrial sectors, energy efficiency, and renewable energy integration in existing building stock.
Dr. Arshad has published close to sixty research articles in top international journals and conferences. He has also authored PRECON, the most comprehensive open residential energy data collection in the world. He is the co-founder of multiple start-up companies in big data, energy analytics and electric vehicle domains. In addition to publishing in top ranked journals and conferences, Dr. Arshad has also authored many reports and white papers for advocacy and evidence-based policy recommendations.
Dr. Arshad has served as consultant to USAID, World Bank Group, GIZ, Energy Department, Hyundai Research, Fatima Group, CPPA and many other national and international agencies.
| Title | Publication | Author | Year |
|---|---|---|---|
| Assessing the Impact of Climate Change on Long Term Load Forecasting for Electric Utilities | Energy Proceedings | Shams N., Ahmad A., Arshad N., | 2025 |
| Multi-objective optimization of battery swapping station to power up mobile and stationary loads | Applied Energy | Gull M.S., Khalid M., Arshad N., | 2024 |
| Sustainable energy transition optimization through decentralized hybrid energy systems with various energy storage technologies under multi-criterion indices: A mid-career repowering scenarios | Journal of Energy Storage | Khan S.N., Abdullah M.A., Nadeem A., Arshad N., | 2024 |
| Graph Convolutional Networks based short-term load forecasting: Leveraging spatial information for improved accuracy | Electric Power Systems Research | Mansoor H., Gull M.S., Rauf H., Shaikh I.U.H., Khalid M., Arshad N., | 2024 |
| Developing a Multipurpose Battery Swapping Station to Energize Mobile and Stationary Loads | Energy Proceedings | Gull M.S., Rauf H., Arshad N., Khalid M., | 2024 |
| Short-Term Load Forecasting Using AMI Data | IEEE Internet of Things Journal | Mansoor H., Ali S., Khan I.U., Arshad N., Khan M.A., Faizullah S., | 2023 |
| A novel smart feature selection strategy of lithium-ion battery degradation modelling for electric vehicles based on modern machine learning algorithms | Journal of Energy Storage | Rauf H., Khalid M., Arshad N., | 2023 |
| Lowering Weighted Average Cost of Generation by Optimizing Operating Time: A Study from Pakistan | 1st International Conference in Advanced Innovation on Smart City, ICAISC 2023 - Proceedings | Khan H.O.A., Ahmad A., Arshad N., Nadeem A., | 2023 |
| Evaluation of single-phase net metering to meet renewable energy targets: A case study from Pakistan | Energy Policy | Tahir M.U., Siraj K., Ali Shah S.F., Arshad N., | 2023 |
| Novel Feature Selection Strategy for Cyclic Loss Prediction of Lithium-ion Electric Vehicle Battery | IEEE Power and Energy Society General Meeting | Rauf H., Khalid M., Arshad N., Pecht M., | 2023 |
| Smart Feature Selection-Based Machine Learning Framework for Calendar Loss Prediction of Li-Ion Electric Vehicle Battery | 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 | Rauf H., Gul M.S., Khalid M., Arshad N., | 2023 |
| Optimizing Renewable Energy Integration for a Sustainable and Resilient Power Sector: Insight Form LPDM Analysis | 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 | Khan H.O.A., Chaudhry T.M., Afaq U., Rauf H., Arshad N., | 2023 |
| Spatio-Temporal Short Term Load Forecasting Using Graph Neural Networks | 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 | Mansoor H., Shabbir M., Ali M.Y., Rauf H., Khalid M., Arshad N., | 2023 |
| Using Clustering to Reduce Models Required for Medium Term Load Forecasting | Proceedings of the International Conference on Optimisation of Electrical and Electronic Equipment, OPTIM | Arif A., Nadeem A., Arshad N., | 2023 |
| PINN with Memory: A Novel Methodology for State of Charge Estimation of Lithium-ion Batteries Under Dynamic Load Profile | IEEE PES Innovative Smart Grid Technologies Conference Europe | Kharal A.Y., Naqvi I.H., Arshad N., | 2023 |
| Performance Evaluation of Low Sampling Rates in Event Detection and Appliance Recognition in Non-Intrusive Load Monitoring System | Proceedings - 2023 IEEE 5th Global Power, Energy and Communication Conference, GPECOM 2023 | Javaid S., Nadeem A., Abdullah M.A., Arshad N., | 2023 |
| Optimization of the battery swapping station to power up mobile and stationary loads | e-Energy 2022 - Proceedings of the 2022 13th ACM International Conference on Future Energy Systems | Gull M.S., Arshad N., | 2022 |
| Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling | Renewable and Sustainable Energy Reviews | Rauf H., Khalid M., Arshad N., | 2022 |
| Soft Load Shedding Based Demand Control of Residential Consumers | Electronics (Switzerland) | Gull M.S., Mehmood N., Rauf H., Khalid M., Arshad N., | 2022 |
| Estimating Battery State of Health using Machine Learning | 2022 10th International Conference on Smart Grid and Clean Energy Technologies, ICSGCE 2022 | Arif A., Hassaan M., Abdullah M., Nadeem A., Arshad N., | 2022 |
| A data-driven approach to reduce electricity theft in developing countries | Utilities Policy | Nadeem A., Arshad N., | 2021 |
| Does Pakistan have enough electricity generation to support massive penetration of electric vehicles? | 2021 IEEE Texas Power and Energy Conference, TPEC 2021 | Iqbal A., Nadeem A., Arslan M.M., Javed M.A., Arshad N., | 2021 |
| Past Vector Similarity for Short Term Electrical Load Forecasting at the Individual Household Level | IEEE Access | Mansoor H., Rauf H., Mubashar M., Khalid M., Arshad N., | 2021 |
| Modelling Residential-Scale Consumer Demographics using Monthly Electricity Consumption Data | 2021 IEEE Electrical Power and Energy Conference, EPEC 2021 | Rahman A., Arif A., Nadeem A., Arshad N., | 2021 |
| Propelling the Penetration of Electric Vehicles in Pakistan by Optimal Placement of Charging Stations ??? | Engineering Proceedings | Khan H.O.A., Saeed F., Arshad N., | 2021 |
