Team of researchers recognized by the American Statistical Association
Prof. Vigor Yang
Prof. Vigor Yang

The scholarship of longtime Daniel Guggenheim School of Aerospace Engineering professor Dr. Vigor Yang was recognized recently by the American Statistical Association with its 2019 Statistics in Physical Engineering Sciences Award.

Yang and seven other Georgia Tech researchers were jointly recognized by the ASA for their paper, "An Efficient Surrogate Model for Emulation and Physics Extraction of Large Eddy Simulations," which was published last year in the Journal of the American Statistical Association.

Joining Yang in this honor are several of his longtime colleagues at Tech: Dr. Simon Mak (ISyE), Chih-Li Sung (ISyE), Dr. Xingjian Wang (AE), Dr. Shiang-Ting Yeh (AE), Dr. Yu-Hung Chang (AE), Prof. V. Roshan Joseph (ISyE), and Prof. C.F. Jeff Wu (ISyE).

The SPES Award is bestowed annually upon a distinguished individual or team whose innovative use of statistics has helped to solve a high-impact problem in the physical and engineering sciences. 

In their article, the team combined engineering physics, computer simulations and statistical modeling to address the need for advanced propulsion and power-generation systems. They proposed a new surrogate model that provides efficient prediction and uncertainty quantification of turbulent flows in swirl injectors with varying geometries, devices commonly used in many engineering applications.

For Yang, the work represented a continuation of his ongoing research initiative, "Data-Enabled Engineering Design Innovation," in which he provided a formal mechanism for integrating data and engineering sciences. Three of the paper's co-authors, Wang, Yeh, and Chang, were advised by Yang as grad students in the AE School.

The research that supported the JASA article was sponsored, in part, by the Air Force Office of Scientific Research and the William R. T. Oakes Endowment of Georgia Institute of Technology. Wu’s work is partially supported by the National Science Foundation.