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.
|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||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||2023|
|Novel Feature Selection Strategy for Cyclic Loss Prediction of Lithium-ion Electric Vehicle Battery||IEEE Power and Energy Society General Meeting||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||2023|
|Short-Term Load Forecasting Using AMI Data||IEEE Internet of Things Journal||2023|
|Spatio-Temporal Short Term Load Forecasting Using Graph Neural Networks||12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023||2023|
|Evaluation of single-phase net metering to meet renewable energy targets: A case study from Pakistan||Energy Policy||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||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||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||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||2022|
|Soft Load Shedding Based Demand Control of Residential Consumers||Electronics (Switzerland)||2022|
|Estimating Battery State of Health using Machine Learning||2022 10th International Conference on Smart Grid and Clean Energy Technologies, ICSGCE 2022||2022|
|A data-driven approach to reduce electricity theft in developing countries||Utilities Policy||2021|
|Does Pakistan have enough electricity generation to support massive penetration of electric vehicles?||2021 IEEE Texas Power and Energy Conference, TPEC 2021||2021|
|Propelling the Penetration of Electric Vehicles in Pakistan by Optimal Placement of Charging Stations ???||Engineering Proceedings||2021|
|Modelling Residential-Scale Consumer Demographics using Monthly Electricity Consumption Data||2021 IEEE Electrical Power and Energy Conference, EPEC 2021||2021|
|Past Vector Similarity for Short Term Electrical Load Forecasting at the Individual Household Level||IEEE Access||2021|
|Fair Allocation Based Soft Load Shedding||Advances in Intelligent Systems and Computing||2021|
|Complementing hydroelectric power with floating solar PV for daytime peak electricity demand||Renewable Energy||2020|
|Economic and Environmental Impact of Vehicle-to-Grid (V2G) Integration in an Intermittent Utility Grid||2020 2nd International Conference on Smart Power and Internet Energy Systems, SPIES 2020||2020|
|Interval forecasting of hourly electricity spot prices using rolling window based gaussian process regression||2020 2nd International Conference on Smart Power and Internet Energy Systems, SPIES 2020||2020|
|Economic Analysis of using Distributed Energy Storage for Frequency Regulation||e-Energy 2020 - Proceedings of the 11th ACM International Conference on Future Energy Systems||2020|
|Design of Solar-Wind Hybrid Power System by using Solar-Wind Complementarity||Proceedings of 2020 4th International Conference on Green Energy and Applications, ICGEA 2020||2020|
|Short term load forecasting on PRECON dataset||2019 International Conference on Advances in the Emerging Computing Technologies, AECT 2019||2020|