70 citations · 71 across the 4 of their papers we have counts for
5 papers
OptAgent: an Agentic AI framework for Intelligent Building Operations
Zixin Jiang, Weili Xu, Bing Dong
The urgent need for building decarbonization calls for a paradigm shift in future autonomous building energy operation, from human-intensive engineering workflows toward intelligen…
BESTOpt: A Modular, Physics-Informed Machine Learning based Building Modeling, Control and Optimization Framework
Zixin Jiang, Ruizhi Song, Guowen Li +5
Modern buildings are increasingly interconnected with occupancy, heating, ventilation, and air-conditioning (HVAC) systems, distributed energy resources (DERs), and power grids. Mo…
Physics-informed machine learning for building performance simulation-A review of a nascent field
Zixin Jiang, Xuezheng Wang, Han Li +5
Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing performance of the built environment, optimizing energy efficiency, im…
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning
Zixin Jiang, Xuezheng Wang, Bing Dong
Physics-informed machine learning (PIML) provides a promising solution for building energy modeling and can serve as a virtual environment to enable reinforcement learning (RL) age…
Modularized Neural Network Incorporating Physical Priors for Smart Building Control, Accuracy or Consistency?
Zixin Jiang, Bing Dong
Model predictive control can achieve significant energy savings, offer grid flexibility, and mitigate carbon emissions. However, the challenge of identifying individual control-ori…