Generative AI as a Multi-Scale Enabler in Guiding the Energy Transition
The global shift towards sustainable and renewable energy systems presents one of the most critical challenges of our time, necessitating innovative approaches that span multiple scales – from atomic to grid-level dynamics. This talk explores how generative AI serves as a transformative tool in this transition by leveraging its capacity to model complex, interconnected systems. This talk explores applications of generative models in accelerating the discovery of innovative materials for energy applications, identifying novel process routes, and helping process integration while addressing process-environment interactions.
Bio: Hariprasad Kodamana is an associate professor with a joint appointment in the Department of Chemical Engineering and the Yardi School of Artificial Intelligence at IIT Delhi, India. His research spans machine learning, optimization and control, and the development of sustainable and net-zero process systems. Kodamana has authored over 100 publications, holds two patents, and has published a book in his research area. He also serves as a subject editor for two international journals in his field.