Murat Keçeli is a Computational Scientist at Argonne National Laboratory. His primary research goal is to accelerate chemical discovery to address the pressing challenges of the 21st century, such as sustainable energy, environmental protection, and advanced materials design. While quantum mechanics provides the fundamental framework for understanding chemical interactions, the complexity of these equations makes exact solutions unattainable, even on the most powerful supercomputers. By developing novel computational methods and integrating artificial intelligence with high-performance computing, Murat aims to overcome these limitations, unlocking new possibilities in materials and molecular discovery. Murat received BS and MS degrees in physics from Bilkent University and a PhD degree in chemical physics from the University of Illinois at Urbana-Champaign. After graduation, he conducted postdoctoral research at MIT and Argonne National Laboratory.
Advances in artificial intelligence are reshaping how scientific discovery can be carried out. By combining accurate physical models, domain-specific AI, autonomous agents, and high-performance computing, we can move beyond individual simulations toward systems that explore large scientific spaces and make decisions about what to compute next. I will discuss this emerging paradigm through examples from computational molecular science, including domain-specific foundation models that approximate expensive quantum-mechanical calculations and ChemGraph, an agentic AI framework for planning and executing scientific workflows. Together, quantum chemistry, AI, agents, and supercomputers offer a path toward more autonomous, scalable, and trustworthy scientific discovery.
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