| Using machine learning techniques for occupancy-prediction-based cooling control in office buildings Y Peng, A Rysanek, Z Nagy, A Schlüter Applied energy 211, 1343-1358, 2018 | 365 | 2018 |
| A critical review of field implementations of occupant-centric building controls JY Park, MM Ouf, B Gunay, Y Peng, W O'Brien, MB Kjærgaard, Z Nagy Building and Environment 165, 106351, 2019 | 268 | 2019 |
| Modeling occupant behavior in buildings S Carlucci, M De Simone, SK Firth, MB Kjærgaard, R Markovic, ... Building and Environment 174, 106768, 2020 | 207 | 2020 |
| A review of select human-building interfaces and their relationship to human behavior, energy use and occupant comfort JK Day, C McIlvennie, C Brackley, M Tarantini, C Piselli, J Hahn, ... Building and environment 178, 106920, 2020 | 178 | 2020 |
| Temperature-preference learning with neural networks for occupant-centric building indoor climate controls Y Peng, Z Nagy, A Schlüter Building and Environment 154, 296-308, 2019 | 133 | 2019 |
| Occupancy learning-based demand-driven cooling control for office spaces Y Peng, A Rysanek, Z Nagy, A Schlüter Building and Environment 122, 145-160, 2017 | 127 | 2017 |
| Hybrid system controls of natural ventilation and HVAC in mixed-mode buildings: A comprehensive review Y Peng, Y Lei, ZD Tekler, N Antanuri, SK Lau, A Chong Energy and Buildings 276, 112509, 2022 | 81 | 2022 |
| A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings Y Lei, S Zhan, E Ono, Y Peng, Z Zhang, T Hasama, A Chong Applied Energy 324, 119742, 2022 | 78 | 2022 |
| Ten questions concerning occupant-centric control and operations Z Nagy, B Gunay, C Miller, J Hahn, MM Ouf, S Lee, BW Hobson, ... Building and Environment 242, 110518, 2023 | 51 | 2023 |
| Comparing the indoor environmental quality of a displacement ventilation and passive chilled beam application to conventional air-conditioning in the Tropics J Pantelic, A Rysanek, C Miller, Y Peng, E Teitelbaum, F Meggers, ... Building and Environment 130, 128-142, 2018 | 37 | 2018 |
| ROBOD, room-level occupancy and building operation dataset ZD Tekler, E Ono, Y Peng, S Zhan, B Lasternas, A Chong Building Simulation 15 (12), 2127-2137, 2022 | 34 | 2022 |
| A hybrid active learning framework for personal thermal comfort models ZD Tekler, Y Lei, Y Peng, C Miller, A Chong Building and Environment 234, 110148, 2023 | 33 | 2023 |
| Experimental assessment of thermal and acoustics interactions on occupant comfort in mixed-mode buildings Y Peng, N Antanuri, SK Lau, B Jebelli, SK Jusuf, C Miller, YT Teo, ... Building and Environment 238, 110342, 2023 | 15 | 2023 |
| Case Study Review: Prediction Techniques in Intelligent HVAC Control Systems Y Peng, A Rysanek, Z Nagy, A Schlueter 9th International Conference on Indoor Air Quality Ventilation and Energy …, 2016 | 14 | 2016 |
| Learning-based demand-driven controls for energy-efficient buildings Y Peng ETH Zurich, 2019 | 3 | 2019 |
| Indoor Environmental Quality assessment of mixed-mode ventilation with ceiling fans in the tropics Y Lei, Y Peng, A Chong E3S Web of Conferences 396, 01086, 2023 | 1 | 2023 |
| Demand-driven building controls: A framework and lessons learnt Y Peng, A Schlüter Innovative Solutions for Energy Transitions: Part IV 5, 844, 2019 | 1 | 2019 |
| Data-driven outdoor and indoor temperature prediction for energy-efficient building operation Y Peng, A Schlüter Innovative Solutions for Energy Transitions: Part III 4, 433, 2019 | | 2019 |