This talk reviews new methodological developments in fusing data science, machine learning, and optimization, as well as their applications in energy systems, mobility, supply chains, fair recommendations. It highlights the symbiotic relationships between deep learning, reinforcement learning, and optimization, through optimization proxies and end-to-end learning.