Harbin Institute of Technology, Shenzhen, Guangdong, China.
Rongpei Shi is a full professor in the College of Materials at Harbin Institute of Technology Shenzhen (HITsz). He received his Ph.D. degree in Materials Science and Engineering from The Ohio State University (OSU) in 2014. Prior to joining HITsz, he was a research associate in the Department of Materials Science and Engineering at OSU from June 2014 to June 2017, and a staff scientist in the Materials Science Division at the Lawrence Livermore National Laboratory (LLNL) from July 2017 to August 2021. His research focuses on the intersection of multi-scale modeling and machine learning, and their applications in understanding composition-processing-microstructure-properties linkages in advanced metallic (Ti, Ni, Co, Cu-based) alloys for structural applications, metal additive manufacturing and energy storage materials. He has published about 80 papers (21 in Acta Materialia with 9 as a first author) in peer-reviewed journals as documented in Google Scholar Profile. He received best poster award in Gordon Research Conference-Physical Metallurgy 2013 and was named among five finalists of Aaronson Award in the International Conference on Solid-Solid Phase Transformation in Inorganic Materials for Materials for outstanding young researcher, at Whistler, Canada on 2015, publication award in physical life and science directorate at LLNL 2021.
The Pennsylvania State University, PA, USA.
Dr. Zi-Kui Liu is the Dorothy Pate Enright Professor in the department of Materials Science and Engineering at The Pennsylvania State University. He obtained his BS from Central South University (China), MS from University of Science and Technology Beijing (China), PhD from Royal Institute of Technology (KTH, Sweden). He was a research associate at University of Wisconsin-Madison and a senior scientist at Questek. He has been at the Pennsylvania State University since 1999 and coined the term "Materials Genome®" in 2002. Dr. Liu's current research activities are centered on first-principles calculations, machine learning, CALPHAD modeling, statistical mechanics, irreversible thermodynamics, and their integration for understanding defects, phase stability, and phase transformations, and designing and tailoring materials chemistry, processing, and properties. He was the lead author of a textbook on Computational Thermodynamics of Materials published by Cambridge University Press.