代表著作

SCI/SCIE 頂尖期刊論文與國際研討會發表

SCI/SCIE 期刊論文

  • 期刊 Energy and Buildings SCI Q1 2025
    Lien, S. K., Canaydin, A., Miller, C., Fu, C., Kazmi, H., & Rajasekharan, J. (2025). Cross-domain disaggregation of electricity for heating in all-electric school buildings–learning from school buildings with district heating. Energy and Buildings, 116359.
    Citations: 0 | Impact Factor: 6.6 | Rank 10/223, Top 5%, in Engineering - Building and Construction
  • 期刊 Energy and Buildings SCI Q1 2024
    Fu, C., Kazmi, H., Quintana, M., & Miller, C. (2024). Creating synthetic energy meter data using conditional diffusion and building metadata. Energy and Buildings, 312, 114216.
    Citations: 10 | Impact Factor: 6.6 | Rank 10/223, Top 5%, in Engineering - Building and Construction
  • 期刊 Energy and Buildings SCI Q1 2024
    Liguori, A., Quintana, M., Fu, C., Miller, C., Frisch, J., & van Treeck, C. (2024). Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight. Energy and Buildings, 310, 114071.
    Citations: 10 | Impact Factor: 6.6 | Rank 10/223, Top 5%, in Engineering - Building and Construction
  • 期刊 Applied Energy SCI Q1 - Top 1% 2024
    Canaydin, A., Fu, C., Balint, A., Khalil, M., Miller, C., & Kazmi, H. (2024). Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data. Applied Energy, 360, 122741.
    Citations: 11 | Impact Factor: 10.1 | Rank 1/223, Top 1%, in Engineering - Building and Construction
  • 期刊 Applied Thermal Engineering SCI Q1 2024
    Fu, C., Quintana, M., Nagy, Z., & Miller, C. (2024). Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation. Applied Thermal Engineering, 236, 121545.
    Citations: 27 | Impact Factor: 6.1 | Rank 3/96, Top 5%, in Chemical Engineering - Fluid Flow and Transfer Processes
  • 期刊 Building and Environment SCI Q1 2023
    Kazmi, H., Fu, C., & Miller, C. (2023). Ten questions concerning data-driven modeling and forecasting of operational energy demand at building and urban scale. Building and Environment, 239, 110407.
    Citations: 40 | Impact Factor: 7.1 | Rank 11/223, Top 5%, in Engineering - Building and Construction
  • 期刊 Science and Technology for the Built Environment SCI 2022
    Miller, C., Picchetti, B., Fu, C., & Pantelic, J. (2022). Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis. Science and Technology for the Built Environment, 1-18.
    Citations: 23 | Impact Factor: 1.7 | Rank 74/223, Top 33%, in Engineering - Building and Construction
  • 期刊 Applied Energy SCI Q1 - Top 1% 2022
    Fu, C., & Miller, C. (2022). Using Google Trends as a proxy for occupant behavior to predict building energy consumption. Applied Energy, 310, 118343.
    Citations: 30 | Impact Factor: 10.1 | Rank 1/223, Top 1%, in Engineering - Building and Construction
  • 期刊 Science and Technology for the Built Environment SCI 2020
    Miller, C., Arjunan, P., Kathirgamanathan, A., Fu, C., Roth, J., Park, J. Y., ... & Haberl, J. (2020). The ASHRAE great energy predictor III competition: Overview and results. Science and Technology for the Built Environment, 26(10), 1427-1447.
    Citations: 88 | Impact Factor: 1.7 | Rank 74/223, Top 33%, in Engineering - Building and Construction

國際研討會論文

  • 會議 CISBAT 2025
    Miller, C., Ibrahim, M., Akbar, I. S., Picchetti, B., Chua, Y. X., Frei, M., ... & Fu, C. The Cool, Quiet City machine learning competition: Overview and results. In 2025 CISBAT.
  • 會議 IEEE PES ISGT EUROPE 2024
    Balint, A., Fu, C., Driesen, J., & Kazmi, H. (2024, October). EnFoBench: A community-driven energy forecasting benchmark. In 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) (pp. 1-5). IEEE.
  • 會議 ACM BuildSys 2023
    Fu, C., Kazmi, H., Quintana, M., & Miller, C. (2023). Enhancing Classification of Energy Meters with Limited Labels using a Semi-Supervised Generative Model. In Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 450-453).
  • 會議 IOP Publishing 2023
    Jin, X., Fu, C., Kazmi, H., Balint, A., Canaydin, A., Quintana, M., ... & Miller, C. (2023, November). The Building Data Genome Directory--An open, comprehensive data sharing platform for building performance research. In Journal of Physics: Conference Series (Vol. 2600, No. 3, p. 032003). IOP Publishing.
  • 會議 ACM BuildSys 2023
    Miller, C., Quintana, M., Frei, M., Chua, Y. X., Fu, C., Picchetti, B., ... & Biljecki, F. (2023, November). Introducing the Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat and Noise with Digital Twin Metrics. In Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 298-299).
  • 會議 ACM BuildSys 2022
    Fu, C., Arjunan, P., & Miller, C. (2022). Trimming outliers using trees: winning solution of the large-scale energy anomaly detection (LEAD) competition. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 456-461).
  • 會議 ASHRAE Annual Conference 2022
    Miller, C., Hao, L., Fu, C. (2022). Gradient boosting machines and careful pre-processing work best: ASHRAE Great Energy Predictor III lessons learned. ASHRAE Annual Conference 2022.