معرفی
Chaobo Zhang is a postdoctoral researcher at the Eindhoven University of Technology, specializing in fast building performance simulation and smart building energy management. He belongs to the Building Performance Group within the Department of the Built Environment.
Education:
- Bachelor in Heating, Ventilation and Air Conditioning, Harbin Institute of Technology (2017)
- PhD in Refrigeration and Cryogenic Engineering, Zhejiang University (2022)
His research integrates artificial intelligence technologies into building systems to enhance energy efficiency and fault detection. Key areas include generative pre-trained transformers (GPT) for energy load prediction, convolutional neural networks for computational fluid dynamics, and domain-specific large language models for HVAC fault diagnosis.
The 15 most recent publications highlight trends in AI-driven building energy management, focusing on technologies like graph convolutional networks for uncertainty quantification, hybrid data-driven physics-based cooling demand models, and self-attention variational autoencoders for digital twin parameter imputation. His work addresses challenges such as data imbalance, federated learning for data silos, and real-time anomaly detection.
Scientific Awards:
- 2020 Best Paper Award, Energy and Built Environment
Chaobo collaborates internationally and contributes to UN Sustainable Development Goals through energy-efficient building technologies. His expertise spans fault detection, machine learning, and computational optimization in building systems.
