Dr. Lee led the R&D team at ATAL to successfully develop an explainable AI platform for energy optimization in central chiller plants. The key innovation is to combine principles of physics with machine learning techniques to better capture the dynamics of chiller plant systems, providing an explainable and highly accurate modelling performance for real-time optimizations. This innovative development helps transform HVAC control from discrete rule-based optimization to holistic data-driven optimization. The platform has been successfully applied to a Grade-A office building in Hong Kong, achieving a further yearly energy saving of 7.52% in 2020.