Contributors
Cai-Zhuang Wang
Principal Investigator
Ames National Laboratory
Distinguished Scientist
wangcz@ameslab.gov
Cai-Zhuang Wang is the lead PI of this project. He has substantial expertise in condensed matter theory and computational materials science. He has extensive experience in materials theory, modeling, and simulation. He has been leading development of novel computational methods including AI/ML assisted framework/workflow for significantly accelerating the materials discovery, design, and synthesis, many-body Gutzwiller wavefunction based ab initio methods for calculation correlated electron materials, adaptive genetic algorithm (AGA) for crystal structure prediction, tight-binding and neural network ML interatomic potentials for reliable molecular dynamics simulations.
Ying Wai Li
Co-Principal Investigator
Los Alamos National Laboratory
Scientist and Team Leader
yingwaili@lanl.gov
Ying Wai Li is a computational statistical physicist with experience in scientific software development for high-performance computers. Her current research interests include machine learning techniques and algorithm development for solving computational physics and materials science problems. She ensures the code produces scientifically important results and leads the Computer Science technical decisions for exa-AMD.
Yongxin Yao
Co-Principal Investigator
Ames National Laboratory
Scientist III
ykent@iastate.edu
Yongxin Yao is a theoretical and computational condensed matter physicist with extensive experience in developing electronic structure methods and computational packages for materials research. His current work focuses on advancing and applying quantum computing and machine learning–enhanced approaches to simulate correlated materials. Yongxin Yao oversees code validation and reliability, continuously identifying functional issues, proposing improvements, and providing feedback on performance and documentation.
Feng Zhang
Co-Principal Investigator
Ames National Laboratory
Scientist II
fzhang@ameslab.gov
Feng Zhang is a computational physicist and materials scientist. His expertise is on multi-scale modeling of materials, ranging from first principes calculations to thermodynamic and kinetic simulations using classical interatomic potentials including those trained by deep neural networks. Feng Zhang helped collect benchmark data on multiple ternary systems for the development of exa-AMD.
Weiyi Xia
Key Personnel
Ames National Laboratory
Scientist I
weiyixia@iastate.edu
Weiyi Xia is a computational physicist with experience in software development for accelerated computational methods. His current research integrates machine learning and novel algorithm development to predict and understand the behavior of complex systems, with a particular interest in magnetic materials and 2D materials. Weiyi Xia focuses on functional implementation, developing new capabilities and ensuring that the exa-AMD workflow produces scientifically accurate and reliable results.
Zhuo Ye
Key Personnel
Ames National Laboratory
Scientist I
zye@iastate.edu
Zhuo Ye is a theoretical and computational physicist with expertise in electronic structure methods and optimization algorithms for materials discovery. Her current research focuses on developing ab initio approaches for correlated systems and high-performance computational frameworks for predicting materials synthesis pathways. Zhuo Ye helped collect benchmark data on multiple ternary systems for the development of exa-AMD.
Maxim Moraru
Key Personnel
Los Alamos National LaboratoryResearch Scientist
moraru@lanl.gov
Maxim Moraru is a computational scientist at Los Alamos National Laboratory with a background in High-Performance Computing. His research interests include high-speed communication, runtime systems, and machine learning models. He investigates scalability and performance, identifying and mitigating bottlenecks to ensure efficient use of computational resources at large scale.