“From Real-World Problems to Esoteric Research: Examples and Personal Experience"

Professor C. F. Jeff Wu holds the Coca-Cola Chair in Engineering Statistics at Georgia Tech and is renowned for his significant contributions to industrial statistics, including pioneering work on the EM algorithm, resampling techniques and robust design. He has received numerous prestigious awards, such as the COPSS Presidents' Award and the Shewhart Medal, and is a fellow of several scholarly societies and a member of both Academia Sinica and the National Academy of Engineering. Notably, Professor Wu introduced the term "Data Science" in 1985, advocating for its recognition within the broader statistical community. He has also supervised 50 Ph.D. students, including 21 who are Fellows of esteemed societies such as ASA, IMS, ASQ, IAQ and IIE, three who are editors of Technometrics, and one who is editor of Journal of Quality Technology.

"Young (and some not-so-young) researchers often wonder how to extract good research ideas and develop useful methodologies from solving real world problems. The path is rarely straightforward and its success depends on the circumstances, tenacity and luck. I will use two examples to illustrate how I trod the path. The first involved an attempt to find optimal growth conditions for nano structures. It led to the development of a new method 'sequential minimum energy design' which exploits an analogy to potential energy of charged particles. After a few years of frustrated efforts and relentless pursuit, we realized that SMED is more suitable for generating samples adaptively to mimic an arbitrary distribution rather than for optimization. The main objective of the second example was to build an efficient statistical emulator based on finite element simulation results with two mesh densities in cast foundry operations. It eventually led to the development of a class of nonstationary Gaussian process models that can be used to connect simulation data of different precisions and speeds. In each example, the developed methodology has broader applications beyond the original problem. I will explain the thought process in each example. Finally, I will share some secrets about a 'path to innovation.'"