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Kazmi, Hussain
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1

Quantifying residential energy flexibility potential for de..:

Kazmi, Hussain ; Mehmood, Fahad ; Shah, Maryam
Energy Policy.  188 (2024)  - p. 114094 , 2024
Link: https://doi.org/10.1016/..
 
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2

Interpretable domain-informed and domain-agnostic features ..:

Canaydin, Ada ; Fu, Chun ; Balint, Attila...
Applied Energy.  360 (2024)  - p. 122741 , 2024
Link: https://doi.org/10.1016/..
 
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3

Deriving Input Variables through Applied Machine Learning f..:

Netzell, Pontus ; Kazmi, Hussain ; Kyprianidis, Konstantinos
Energies.  17 (2024)  10 - p. 2246 , 2024
Link: https://doi.org/10.3390/..
 
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4

Beyond empirical risk: testing data-driven energy models in..:

, In: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems,
Kazmi, Hussain ; Balint, Attila ; Jiang, Fuyang.. - p. 692-695 , 2024
Link: https://dl.acm.org/doi/1..
 
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5

Creating synthetic energy meter data using conditional diff..:

Fu, Chun ; Kazmi, Hussain ; Quintana, Matias.
Energy and Buildings.  312 (2024)  - p. 114216 , 2024
Link: https://doi.org/10.1016/..
 
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6

Modelling electricity demand in Karachi: historical trends,..:

, In: 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East),
Kazmi, Hussain ; Mehmood, Fahad - p. 1-5 , 2023
Link: https://doi.org/10.1109/..
 
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7

Developing energy flexibility in clusters of buildings: A c..:

Le Dréau, Jérôme ; Lopes, Rui Amaral ; O'Connell, Sarah...
Energy and Buildings.  300 (2023)  - p. 113608 , 2023
Link: https://doi.org/10.1016/..
 
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8

The Forecastability of Underlying Building Electricity Dema..:

, In: 2023 IEEE International Conference on Big Data (BigData),
Khalil, Mohamad ; Stephen McGough, A. ; Kazmi, Hussain. - p. 3785-3793 , 2023
Link: https://doi.org/10.1109/..
 
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9

Physics-informed model-based reinforcement learning (PI-MBR..:

, In: Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation,
Saeed, Muhammad Hafeez ; Kazmi, Hussain ; Deconinck, Geert - p. 300-302 , 2023
Link: https://dl.acm.org/doi/1..
 
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10

Ten questions concerning data-driven modelling and forecast..:

Kazmi, Hussain ; Fu, Chun ; Miller, Clayton
Building and Environment.  239 (2023)  - p. 110407 , 2023
Link: https://doi.org/10.1016/..
 
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11

Enhancing Classification of Energy Meters with Limited Labe..:

, In: Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation,
Fu, Chun ; Kazmi, Hussain ; Quintana, Matias. - p. 450-453 , 2023
Link: https://dl.acm.org/doi/1..
 
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12

Using domain-augmented federated learning to model thermost..:

, In: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE),
Balint, Attila ; Raja, Haroon ; Driesen, Johan. - p. 1-1 , 2023
Link: https://doi.org/10.1109/..
 
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13

A Global Data-driven Forecasting Approach for Buildings Ene..:

, In: 2023 IEEE 6th International Conference on Big Data and Artificial Intelligence (BDAI),
Khalil, Mohamad ; McGough, A. Stephen ; Kazmi, Hussain. - p. 50-55 , 2023
Link: https://doi.org/10.1109/..
 
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14

On the causality of data-driven building thermal models:

, In: Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation,
Jiang, Fuyang ; Driesen, Johan ; Kazmi, Hussain - p. 454-457 , 2023
Link: https://dl.acm.org/doi/1..
 
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15

The Building Data Genome Directory – An open, comprehensive..:

Jin, Xiaoyu ; Fu, Chun ; Kazmi, Hussain...
Journal of Physics: Conference Series.  2600 (2023)  3 - p. 032003 , 2023
Link: https://doi.org/10.1088/..
 
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