On January 22nd, Professor Byeng Dong Youn of Seoul National University visited the Joint Institute and gave a seminar. His team and JI Prof. Mian Li’s Intelligent Design and optimization Laboratory (iDO Lab) then signed a MOU to collaborate on the research of prognostics and health management and risk assessment.
The memorandum of understanding stipulates that the scope of the collaborative projects includes but not limited to health prognostics and management of mechanical components, health prognostics and diagnostics of energy storage systems, and physics-of-failure modeling. Based on the MOU, both parties hope to develop mutually beneficial long-term collaboration and exchange.

DSC0021副本Prof. Byeng Dong Youn giving a seminar

DSC_0039副本Prof. Mian Li (right 4th) and Prof. Byeng Dong Youn (right 3rd) and teams at the MOU signing

Background information

Professor Byeng D. Youn is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Seoul National University and an Advisory Board Member of Samsung Electronics since 2012. He earned Ph.D. from the University of Iowa in 2001. His current research interests include system risk-based design, prognostics and health management (PHM), reliability engineering and design, uncertainty quantification and management, decision-based design under uncertainty, and energy harvesting. His dedication and efforts in research have garnered substantive peer recognition resulting in many notable awards. His research has been funded by numerous international agencies and he is serving as an Associate Editor in many premier international journals.
Intelligent Design and optimization Laboratory (iDO Lab) focuses on providing intelligent solutions to multifarious (especially inter- and multi-disciplinary) problems that are encountered in various aspects of complex system design and analysis. Topics include (but are not limited to): new product development, robust design, system configuration improvement, reliability and sensitivity analysis, competitive marketing and multi-disciplinary design optimization.  We aim to develop and employ a wide range of novel optimization and analysis techniques to aid in advanced decision making, using linear and non-linear optimization paradigms, approximation methods, simulation, evolutionary- and heuristic- based algorithms, in addition to numerous other models and approaches, under both deterministic and stochastic conditions.
Lab website:http://umji.sjtu.edu.cn/personal/mian-li/index.php/zh/