Shyue Ping Ong, UC San Diego
Meet: https://meet.google.com/niy-gtpk-sro
YouTube Stream: https://youtube.com/live/6p53814yMXs
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Abstract:
In silico materials design requires navigating vast and diverse chemical spaces. While ab initio methods have been transformative for materials simulations, their high computational cost and poor scaling limit their reach. In this talk, I will introduce foundational potentials (FPs), i.e., machine learning interatomic potentials with near-universal coverage of the periodic table. Acting as efficient surrogates for expensive ab initio calculations, FPs enable exploration of the materials universe at unprecedented scales and accuracy. I will outline the physics-informed AI architectures that underpin these models, highlight recent advancements, and demonstrate their impact on large-scale materials design. I will also discuss the remaining challenges and opportunities for FPs, and share perspectives on how to maximize the “return on data” in materials R&D.
Bio:
Shyue Ping Ong is a professor in the Aiiso Yufeng Li Family Department of Chemical and Nano Engineering at the University of California, San Diego. He earned his PhD from the Massachusetts Institute of Technology in 2011 and leads the Materials Virtual Lab, an interdisciplinary research group applying materials science, computer science, and data science to accelerate materials discovery and design. Ong is a leading researcher in the application of AI and machine learning to materials design. He pioneered the concept of foundational potentials with universal coverage of the periodic table, which have transformed the scale and speed of materials exploration. He is also well-known for his efforts in democratizing access to materials data and software. He is one of the founding developers of the Materials Project and the founder of Python Materials Genomics (pymatgen), an open-source materials analysis library used by hundreds of thousands of researchers worldwide. Ong has published more than 170 articles in materials informatics and has been named a Clarivate Highly Cited Researcher since 2021. He is a recipient of the prestigious U.S. Department of Energy Early Career Research Program and the Office of Naval Research Young Investigator Program awards.