Zhenyu Kong

Zhenyu "James" Kong is the Ralph H. Bogle Professor in the Department of Industrial and Systems Engineering at Virginia Tech's College of Engineering. With over 20 years of academic experience, he has established himself as a leading researcher in manufacturing systems engineering with a focus on smart manufacturing technologies.

Dr. Kong received his Ph.D. in Industrial and Systems Engineering from the University of Wisconsin-Madison in 2004, following Master's and Bachelor's degrees in Mechanical Engineering from Harbin Institute of Technology in China. His academic career includes professorial positions at Virginia Tech since 2006 and previously at Oklahoma State University.

His research focuses on the intersection of machine learning, cyber-physical systems, and manufacturing engineering. Specifically, he investigates real-time sensing, advanced analytics, and process monitoring/control for smart manufacturing systems. His work on modeling, synthesis, and diagnosis for large and complex manufacturing systems has significantly advanced the field of additive manufacturing quality control, with particular emphasis on applying deep learning techniques to defect detection and process optimization.

Dr. Kong's research has been supported by major funding agencies including the Department of Defense, National Science Foundation, Department of Energy, and Office of Naval Research. His publications demonstrate a consistent focus on applying machine learning to solve practical manufacturing challenges, particularly in additive manufacturing quality control and process monitoring.

• Fellow of Institute of Industrial and Systems Engineers (IISE), 2020
• Dean's Award for Excellence in Research, College of Engineering, Virginia Tech, 2019
• Multiple Best Paper Awards from IISE Transactions and INFORMS conferences (2015-2020)
• APM Outstanding Faculty Award, Virginia Tech, 2018
• Halliburton Outstanding Faculty Award, Oklahoma State University, 2013

As an educator, Dr. Kong has taught courses including Advanced Topics in Manufacturing Systems Engineering, Sensing and Data Analytics for Complex Systems, and Statistical Quality Control. He leads the SMART Lab at Virginia Tech, where his research group develops innovative solutions for manufacturing challenges using cutting-edge data analytics and machine learning techniques. His research has been featured multiple times in ISE Magazine, highlighting its practical significance and impact on manufacturing industry practices.