Anh Tran
Scientific Machine Learning
Scientific Machine Learning
Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-1323
Biography
Anh Tran joined Sandia National Laboratories (Albuquerque, NM) as a postdoctoral appointee in January 2019 and became a staff member at the Center of Computing Research since September 2020. He has worked at the Uncertainty Quantification and Optimization department, as well as the Scientific Machine Learning department. His wide research interest include optimization, optimal experimental design, machine learning, and uncertainty quantification methodologies for multiscale computational materials science applications.
In the last few years, he has been focusing on Gaussian process regression and Bayesian optimization, as well as uncertainty quantification applications for materials science at multiple length-scales and time-scales for materials design. Some applications include phase-field simulation, kinetic Monte Carlo, molecular dynamics, and crystal plasticity finite element.
He is a member of ASME, TMS, SIAM, and USACM.
Education
Ph.D., Mechanical Engineering, Georgia Institute of Technology, Dec 2018.
M.S., Mechanical Engineering, Georgia Institute of Technology, May 2018.
M.S., Mathematics, Georgia Southern University, May 2014.
B.S., Mechanical Engineering, Georgia Institute of Technology, Dec 2011.