Zeng Peng

I am currently a Ph.D. student at the Division of Building Technology and Design.

My goal is turning buildings and energy networks into interactive AI agents that sense, think, plan and act.

My work focuses on integrating advanced AI technologies, such as large language models and deep learning, with modern building and energy systems. Recent researches span semantic data modelling (s223p/BRICK/REC), LLM-driven data understanding and automation, fault detection and diagnosis (FDD), anomaly detection, generative building semantic model creation, and federated learning. This interdisciplinary approach aims to revolutionize how we interact with and optimize built environments.