Our research bridges quantum chemistry (QC), machine learning (ML) and artificial intelligence (AI), and chemical understanding to solve the world’s most pressing problems: Energy supply and climate change. Our approaches build on the growing computing power to achieve Virtual High Throughput Screening (VHTS), which is complemented to the ample literature precedents to arrive at Property-constrained Deep Generative Models (pDGMs) for molecular design or is directly trained for Machine Learning (ML) Property Prediction. We further combine QC and ML to derive chemical understanding to foster comprehensions of chemical reactions and molecular design.