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Hieu-Chi Dam is Professor in the School of Knowledge Science at the Japan Advanced Institute of Science and Technology (JAIST). He earned a Bachelor of Science in Physics from the University of Tokyo in 1998, a Master of Science in Materials Science from JAIST in 2000, and a Doctor of Philosophy in Materials Science from JAIST in 2003. Prior to his current role, he served as Associate Professor at JAIST from 2011 to 2020 and held earlier positions including Lecturer at the Department of Physics, Hanoi National University, and various appointments at JAIST starting in 2004. Since 2021, he has also held a professorship at Tohoku University in the International Center for Synchrotron Radiation Innovation Smart Cross Fertilization Division.
Dam’s research centers on data science and materials informatics, with specializations in computational science, magnetism, superconductivity, strongly correlated systems, applied materials, and mathematical physics. His work integrates first-principles calculations, data mining, machine learning, and diffraction physics to advance materials discovery, including studies on alloy properties, catalyst degradation, and AI-driven frameworks for high-entropy alloys. He has contributed to numerous peer-reviewed publications on topics such as ensemble learning for rare-earth transition-metal alloys and unsupervised learning approaches to materials imaging data. Dam has received recognition including an Excellent Oral Presentation award at the ACCMS-Theme Meeting on Multiscale Modelling of Materials for Sustainable Development in 2018 and participates in conference activities and academic presentations in his field.
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JAIST researchers unveil an AI framework blending data and expert knowledge via LLMs and Dempster-Shafer theory, slashing HEA discovery time with 86-92% accuracy on novel compositions.
Explore JAIST's groundbreaking AI framework for high-entropy alloys discovery, fusing data and literature for uncertainty-aware predictions. Implications for Japan higher ed research.
Explore how researchers at JAIST and Tohoku University developed an AI framework fusing data and literature to speed high-entropy alloy discovery, with implications for Japanese higher education.
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