| Understanding the energy consumption and occupancy of a multi-purpose academic building MS Gul, S Patidar Energy and Buildings 87, 155-165, 2015 | 428 | 2015 |
| A deep convolutional neural network model for rapid prediction of fluvial flood inundation S Kabir, S Patidar, X Xia, Q Liang, J Neal, G Pender Journal of Hydrology 590, 125481, 2020 | 161 | 2020 |
| Probabilistic climate projections with dynamic building simulation: Predicting overheating in dwellings DP Jenkins, S Patidar, PFG Banfill, GJ Gibson Energy and Buildings 43 (7), 1723-1731, 2011 | 96 | 2011 |
| Synthesising electrical demand profiles for UK dwellings DP Jenkins, S Patidar, SA Simpson Energy and Buildings 76, 605-614, 2014 | 51 | 2014 |
| Methods for assessing domestic overheating for future building regulation compliance DP Jenkins, V Ingram, SA Simpson, S Patidar Energy Policy 56, 684-692, 2013 | 44 | 2013 |
| Statistical techniques to emulate dynamic building simulations for overheating analyses in future probabilistic climates S Patidar, DP Jenkins, GJ Gibson, PFG Banfill Journal of Building Performance Simulation 4 (3), 271-284, 2011 | 41 | 2011 |
| Understanding residential occupant cooling behaviour through electricity consumption in warm-humid climate KB Debnath, DP Jenkins, S Patidar, AD Peacock Buildings 10 (4), 78, 2020 | 32 | 2020 |
| A multi-sectoral approach to modelling community energy demand of the built environment P McCallum, DP Jenkins, AD Peacock, S Patidar, M Andoni, D Flynn, ... Energy Policy 132, 865-875, 2019 | 30 | 2019 |
| Method for incorporating morphological sensitivity into flood inundation modeling D Pender, S Patidar, K Hassan, H Haynes Journal of Hydraulic Engineering 142 (6), 04016008, 2016 | 25 | 2016 |
| Stochastic modelling techniques for generating synthetic energy demand profiles S Patidar, DP Jenkins, SA Simpson International Journal of Energy and Statistics 4 (03), 1650014, 2016 | 24 | 2016 |
| Simple statistical model for complex probabilistic climate projections: Overheating risk and extreme events S Patidar, D Jenkins, P Banfill, G Gibson Renewable Energy 61, 23-28, 2014 | 24 | 2014 |
| Stochastic simulation of daily streamflow sequences using a hidden Markov model D Pender, S Patidar, G Pender, H Haynes Hydrology Research 47 (1), 75-88, 2016 | 23 | 2016 |
| Spatial distribution based on optimal interpolation techniques and assessment of contamination risk for toxic metals in the surface soil A Saha, BS Gupta, S Patidar, N Martínez-Villegas Journal of South American Earth Sciences 115, 103763, 2022 | 22 | 2022 |
| Investigating capabilities of machine learning techniques in forecasting stream flow S Kabir, S Patidar, G Pender Proceedings of the Institution of Civil Engineers-Water Management 173 (2 …, 2020 | 20 | 2020 |
| Developing a probabilistic tool for assessing the risk of overheating in buildings for future climates DP Jenkins, S Patidar, P Banfill, G Gibson Renewable energy 61, 7-11, 2014 | 20 | 2014 |
| A machine learning approach for forecasting and visualising flood inundation information S Kabir, S Patidar, G Pender Proceedings of the Institution of Civil Engineers-Water Management 174 (1 …, 2021 | 19 | 2021 |
| Tailoring a future overheating risk tool for existing building design practice in domestic and non-domestic sectors M Gul, DP Jenkins, S Patidar, PFG Banfill, G Menzies, G Gibson Building Services Engineering Research and Technology 33 (1), 105-117, 2012 | 18 | 2012 |
| The impact of climate change on hydroecological response in chalk streams A Visser, L Beevers, S Patidar Water 11 (3), 596, 2019 | 17 | 2019 |
| Quantifying change in buildings in a future climate and their effect on energy systems DP Jenkins, S Patidar, SA Simpson Buildings 5 (3), 985-1002, 2015 | 16 | 2015 |
| Macro‐invertebrate community response to multi‐annual hydrological indicators A Visser, L Beevers, S Patidar River research and applications 33 (5), 707-717, 2017 | 15 | 2017 |
David Paul JenkinsHeriot-Watt UniversityVerified email at hw.ac.uk
