Yan Wang, from BJUT's Faculty of Science, (and collaborators from Georgia Tech and Boeing Company）wins the 2022 Statistics in Physical Engineering (SPES) Award from the American Statistical Association (ASA), for the paper "Effective model calibration via sensible variable identification and adjustment with application to composite fuselage simulation". This paper is published in the prestigious journal Annals of Applied Statistics.（Wang, Y.; Yue, X.; Tuo, R.; Hunt, J.H.; Shi, J. Effective model calibration via sensible variable identification and adjustment with application to composite fuselage simulation. Ann. Appl. Stat. 2020, 14(4), 1759–1776.）

The SPES Award is presented annually to an outstanding paper for its innovative use of statistics to address high-impact problems in the physical and engineering sciences.      

In this work, Yan Wang and her collaborators introduced engineering design knowledge into the calibration of computer models. They proposed an efficient calibration method that can identify and estimate the sensible calibration parameters with limited physical experimental data. This approach has been successfully applied to a composite fuselage simulation problem.