Area of research
Statistics, Probability and Uncertainty · Computational Theory and Mathematics
Research interest
Research interests include Computer science, Surrogate model, Prognostics, Process (computing), Data science, and Artificial intelligence.
Combined effect of random porosity and surface defect on fatigue lifetime of additively manufactured micro-sized Ti6Al4V components: An investigation based on numerical analysis and machine learning approach
A Physics-Constrained Bayesian neural network for battery remaining useful life prediction
Corrosion morphology prediction of civil infrastructure using a physics-constrained machine learning method
A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies
A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives
Bayesian model updating with finite element vs surrogate models: Application to a miter gate structural system
Surrogate Modeling of Nonlinear Dynamic Systems: A Comparative Study
Probabilistic damage detection using a new likelihood-free Bayesian inference method
Diagnostics and prognostics of multi-mode failure scenarios in miter gates using multiple data sources and a dynamic Bayesian network
Experimental study on effect of additional torsional load on bending fatigue behavior and failure mechanism of steel wire rope