Guannan Zhang, Ph.D. - Research Group

Research Group

Postdoctoral Scholar in Computer Science and Mathematics Division at ORNL

Ph.D. in Applied Mathematics, Michigan Technological University, 2020.
Research area: inverse problems, probabilistic generative models.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Postdoctoral Scholar in Computer Science and Mathematics Division at ORNL

Ph.D. in Applied Mathematics, Florida State University, 2023.
Research area: AI/ML for data assimilation and uncertainty quantification.
Funding support: DOE Early Career project "Advanced UQ methods for Scientific Inverse Problems".

Postdoctoral Scholar in Center for Nanophase Materials Sciences at ORNL (co-supervised with Dr. Miaofang Chi)

Ph.D. in Material Science and Engineering, North Carolina State University, 2023.
Research area: Development and characterization of new materials; AI/ML for analysis of microscopy data and control of microscopy experimentation.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Postdoctoral Scholar in Neutron Scattering Division at ORNL (co-supervised with Dr. Huibo Cao)

Ph.D. in Condensed Matter and Materials Physics, McMaster University, 2021.
Research area: Use neutron scattering facility on superconductivity, topological insulators; AI/ML and optimization method to fundamental physics phenomenon such as crystal electric field excitation.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Postdoctoral Scholar in Neutron Scattering Division at ORNL (co-supervised with Dr. Xiaoping Wang)

Ph.D. in Chemistry, University of Warsaw, 2023.
Research area: Quantum crystallography methods to detect relativistic effects in crystal strutures.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Ph.D. Student in Applied Mathematics at Auburn University

Co-supervised with Prof. Yanzhao Cao at Auburn University.
Research area: Probabilistic generative models such as normalizing flows and diffusion models.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Postdoctoral Scholar in Neutron Scattering Division at ORNL (co-supervised with Dr. Huibo Cao, 2021 - 2023)

Ph.D. in Condensed Matter Physics, Fudan University, 2021.
Research area: Magnetic properties of quantum materials such as frustrated magnets and multiferroic materials; AI/ML for automation of neutron scattering experimentation.
Funding support: DOE ASCR SciML project: "Machine Learning for Scientific Data Analytics at DOE User Facilities".

Postdoctoral Scholar in Computer Science and Mathematics Division at ORNL (2020-2022)

Ph.D. in Mechanical Engineering, Johns Hopkins University, 2020.
Current Position: Senior Data Scientist at Walmart Global Tech, Mountain View, CA.

Ph.D. Student in Applied Mathematics at Auburn University (2015-2019)

Co-supervised with Prof. Yanzhao Cao at Auburn University.
Current Position: Associate Staff Scientist in Fusion Energy Science Division at ORNL.

Yuwei Geng, Department of Mathematics, University of South Carolina, 2024
Ali Haisam Muhammad, Department of Computer Science, Virginia Tech, 2024
Siming Liang, Department of Mathematics, Florida State University, 2024
Yao Yao, Department of Mathematics, University of Iowa, 2023.
Augustine Twumasi, Department of Mathematics, University of Texas El Paso, 2023.
Jacob Smith, Material Science and Engineering Department, North Carolina State University, 2022-2023.
Zhaiming Shen, Department of Mathematics, University of Georgia, 2022.
Siyan Liu, Department of Chemical and Petroleum Engineering, University of Kansas, 2019.
Kan Zhang, Department of Mathematics, Illinois Institute of Technology, 2019.
Sirui Bi, Department of Mechanical Engineering, Johns Hopkins University, 2019.
Jie Yang, Department of Mathematics, Shandong University, 2016.