Zi-Kui Liu | Professor of Materials Science and Engineering
Pennsylvania State University

Zi-Kui Liu, Professor of Materials Science and Engineering, Pennsylvania State University

Zi-Kui Liu is Professor of Materials Science and Engineering at The Pennsylvania State University. He joined Penn State in 1999 after receiving his education in China and Sweden and working at the University of Wisconsin-Madison and QuesTek Innovations. He has been the Editor-in-Chief of CALPHAD since 2000 and coined the term Materials Genome® in 2002. Professor Liu led the establishment of the NSF Industry-University Cooperative Research Center for Computational Materials Design and served as its director from 2005 to 2014. His team developed Zentropy Theory, which integrates quantum mechanics, statistical mechanics, and thermodynamics for quantitative prediction of emergent behaviors through free-energy landscapes and provides an all-scale, pan-disciplinary framework for understanding information, emergence, and intelligence across physical, biological, social, and engineered systems. He also developed the Theory of Cross Phenomena, extending thermodynamic principles to transport processes and complex systems. Professor Liu served as the 100th President of ASM International and founded the journal ZENtropy, where he serves as Editor-in-Chief. Recent innovations from his group and collaborators have led to ZENN, a thermodynamics-inspired artificial intelligence framework that embeds principles from Zentropy Theory into machine learning, enabling robust learning from heterogeneous data, advancing explainable AI and AI safety, and resulting in three provisional patent applications. Professor Liu envisions the future of intelligence as a thermodynamically guided partnership between human and artificial intelligence, enabling a new era of knowledge creation, scientific discovery, and innovation across scales and disciplines.

Appearances:



Day 2: 29th October @ 10:00

Human Intelligence + Artificial Intelligence: A Pan-Disciplinary Framework for the Future of Intelligence

Artificial intelligence (AI) and human intelligence (HI) share deep thermodynamic roots: both transform energy, information, and uncertainty into organized, predictive structures. This presentation introduces Zentropy Theory, which integrates quantum mechanics, statistical mechanics, and thermodynamics into an all-scale, pan-disciplinary framework for predicting emergence. Building on this framework, I will discuss recent advances toward a new generation of AI grounded in thermodynamic principles, including ZENN and ZeGNN, which unify energy, entropy, information, and intelligence while providing intrinsic mechanisms for explainability, stability, and AI safety. The talk explores how thermodynamics can guide the convergence of HI and AI, enabling a new era of scientific discovery, innovation, and knowledge creation across disciplines.

last published: 07/Sep/26 12:05 GMT

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