1. Taheri, S., Hosseini, P., & Razban, A. (2022). Model predictive control of heating, ventilation, and air conditioning (HVAC) systems: A state-of-the-art review. Journal of Building Engineering, 60, 105067.
Cited by: 254
2. Taheri, S., & Razban, A. (2021). Learning-based CO₂ concentration prediction: Application to indoor air quality control using demand-controlled ventilation. Building and Environment, 205, 108164.
Cited by: 194
3. Movahed, P., Taheri, S., & Razban, A. (2023). A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems. Applied Energy, 339, 120948.
Cited by: 60
4. Trautman, N., Razban, A., & Chen, J. (2021). Overall chilled water system energy consumption modeling and optimization. Applied Energy, 299, 117166.
Cited by: 46
5. Hosseini, P., Taheri, S., Akhavan, J., & Razban, A. (2023). Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting. Energy Conversion and Management, 283, 116900.
Cited by: 39
Dr. Ali Razban’s research advances sustainable building technologies through intelligent control, IoT-enabled sensing, and data-driven modeling, reducing energy consumption while improving indoor environmental quality. His work bridges academia and industry to accelerate the transition toward smart, low-carbon infrastructure