Enhancing Machine Learning Interpretability in HVAC Controls Through Generative AI: Breakthroughs by BSEG Alumni and Researcher 

BSEG alumni Prof. Liang Zhang from the University of Arizona and current BSEG Research Scientist Dr. Zhelun “Aaron” Chen explored the use of large language model for enhancing interpretability of machine learning-based HVAC control. Their results indicated that, with the help of large language model or generative AI, the rationale of the machine learning can be better explained. Their findings have been published by Energy & Buildings. 

Link to publication: Large language model-based interpretable machine learning control in building energy systems (https://www.sciencedirect.com/science/article/abs/pii/S0378778824003943?via=ihub