Runyuan Guo received the B.S. degree in measurement and control technology from Chongqing University of Technology, Chongqing, China, in 2014, and the M.S. and Ph.D. degrees in control science and engineering from the Xi'an University of Technology (XUT), Xi'an, China, in 2018 and 2023, respectively. He was the holder of the China Instrument and Control Society Scholarships and the National Scholarship from the Ministry of Educational of China. He was awarded the Outstanding Paper of the Year by the Chinese Journal of Scientific Instrument in 2019 and the Frontrunner 5000 (Top Articles from Outstanding S&T Journals of China) in 2021. He is currently a Lecturer with XUT and a youth editorial board member for Instrumentation and Journal of Measurement Science and Instrumentation. His research interests mainly include deep learning-based soft sensor, computer vision-based welding defect detection, safety and reliability of data-driven industrial process monitoring/defect detection/soft sensor/fault diagnosis models, and adversarial machine learning.
Han Liu received the B.S. degree in automation from the Shaanxi Provincial Institute of Mechanical Engineering, Xi’an, China, in 1993, and the M.S. and Ph.D. degrees in control science and engineering from the Xi’an University of Technology, Xi’an, in 1996 and 2003, respectively. He is currently a Professor with the School of Automation and Information Engineering, Xi’an University of Technology. He has authored more than 120 journal and conference papers. His research interests include industrial artificial intelligence, machine learning, pattern recognition, soft sensor, intelligent information processing, and nonlinear system control.
