Imagine a groundbreaking methodology that revolutionizes the way industries monitor and control their processes—this is the essence of Dr. Jianjun Shi's innovation. 

The American Society for Quality (ASQ) has awarded Dr. Jianjun Shi the Shainin Medal "for his invention and implementation of in-process quality improvement methodologies that integrate data science and systems theory to analyze in-process sensing data, enabling root cause diagnosis, automatic compensation, and defect prevention across the automotive, aerospace, steel mill, and semiconductor industries.” 

Each year, only one nominee receives this prestigious award, based on the criteria that a unique and/or creative method for improving quality or products, processes, or services has been developed.  

Dr. Jianjun Shi is the Carolyn J. Stewart Chair and Professor in the H. Milton School of Industrial and Systems Engineering, with joint appointment in the Woodruff School of Mechanical Engineering. Dr. Shi is a pioneer in the application of data fusion for quality improvements, and his work in the development and implementation of in-process quality improvement (IPQI) methodologies puts an innovative spin on the traditional quality control concepts. Dr. Shi’s methodology focuses on integrating data science and system theory to achieve process monitoring, diagnosis, and control.