| Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems H Kazmi, F Mehmood, S Lodeweyckx, J Driesen Energy 144, 159-168, 2018 | 107 | 2018 |
| Generalizable occupant-driven optimization model for domestic hot water production in NZEB H Kazmi, S D’Oca, C Delmastro, S Lodeweyckx, SP Corgnati Applied Energy 175, 1-15, 2016 | 93 | 2016 |
| Multi-agent reinforcement learning for modeling and control of thermostatically controlled loads H Kazmi, J Suykens, A Balint, J Driesen Applied energy 238, 1022-1035, 2019 | 81 | 2019 |
| Deep reinforcement learning for optimal control of space heating A Nagy, H Kazmi, F Cheaib, J Driesen arXiv preprint arXiv:1805.03777, 2018 | 68 | 2018 |
| Transfer learning in demand response: A review of algorithms for data-efficient modelling and control T Peirelinck, H Kazmi, BV Mbuwir, C Hermans, F Spiessens, J Suykens, ... Energy and AI 7, 100126, 2022 | 67 | 2022 |
| Towards data-driven energy communities: A review of open-source datasets, models and tools H Kazmi, Í Munné-Collado, F Mehmood, TA Syed, J Driesen Renewable and Sustainable Energy Reviews 148, 111290, 2021 | 63 | 2021 |
| Determinants of energy flexibility in residential hot water systems A Balint, H Kazmi Energy and Buildings 188, 286-296, 2019 | 52 | 2019 |
| Electricity load-shedding in Pakistan: Unintended consequences, opportunities and policy recommendations H Kazmi, F Mehmood, Z Tao, Z Riaz, J Driesen Energy Policy 128, 411-417, 2019 | 50 | 2019 |
| Review of applied and tested control possibilities for energy flexibility in buildings C Finck, P Beagon, J Claus, T Pean, P Vogler-Finck, K Zhang, HS Kazmi Review of applied and tested control possibilities for energy flexibility in …, 2018 | 42 | 2018 |
| Teaching robots a lesson: determinants of robot punishment M Keijsers, H Kazmi, F Eyssel, C Bartneck International Journal of Social Robotics 13, 41-54, 2021 | 31 | 2021 |
| Estimating occupancy from measurements and knowledge using the bayesian network for energy management M Amayri, S Ploix, H Kazmi, QD Ngo, EL Safadi Journal of Sensors 2019, 2019 | 22 | 2019 |
| Smart home futures: Algorithmic challenges and opportunities H Kazmi, F Mehmood, M Amayri 2017 14th International Symposium on Pervasive Systems, Algorithms and …, 2017 | 18 | 2017 |
| Cloud-based sentiment analysis for interactive agents M Keijsers, C Bartneck, HS Kazmi Proceedings of the 7th international conference on human-agent interaction …, 2019 | 17 | 2019 |
| How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead H Kazmi, Z Tao Applied Energy 323, 119565, 2022 | 15 | 2022 |
| Demonstrating model-based reinforcement learning for energy efficiency and demand response using hot water vessels in net-zero energy buildings H Kazmi, S D'Oca 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2016 | 14 | 2016 |
| Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale H Kazmi, C Fu, C Miller Building and Environment 239, 110407, 2023 | 13 | 2023 |
| Principles of energy flexible buildings: energy in buildings and communities programme annex 67 energy flexible buildings AJ Marszal-Pomianowska, H Johra, A Knotzer, J Salom, T Péan, ... International Energy Agency, 2020 | 13* | 2020 |
| Minimizing grid interaction of solar generation and DHW loads in nZEBs using model-free reinforcement learning A Ali, H Kazmi Data Analytics for Renewable Energy Integration: Informing the Generation …, 2017 | 13 | 2017 |
| Energy balances, thermal performance, and heat stress: Disentangling occupant behaviour and weather influences in a Dutch net-zero energy neighborhood H Kazmi, M Keijsers, F Mehmood, C Miller Energy and Buildings 263, 112020, 2022 | 12 | 2022 |
| Automated demand side management in buildings H Kazmi, J Driesen Artificial Intelligence Techniques for a Scalable Energy Transition …, 2020 | 12 | 2020 |
Johan DriesenKU Leuven & EnergyVilleVerified email at esat.kuleuven.be
