Location: Virtual
The Joint CARTE (University of Toronto) and University of Seoul Applied AI/DS seminar series welcomes Professor Chi-Guhn Lee.
Registration: Please register through this link.
Abstract: Complex systems we face today consists of numerous sub-systems and components, and its continuous operation depends on that of sub-systems and components. As such, we at C-MORE (Centre for Maintenance Optimization and Reliability Engineering) have made significant research efforts in physical asset management by applying machine learning to asset condition monitoring and optimal maintenance recommendations. In this talk, we will cover fundamental notions of machine learning and its application to asset management. As part of the talk we will share multiple case studies as well as advanced algorithms developed
Bio: Dr. Chi-Guhn Lee is a Professor of Industrial Engineering and the Director of the Centre for Maintenance Optimization and Reliability Engineering (C-MORE) at the University of Toronto. Dr. Lee received a Ph.D. in Industrial and Operations Engineering at the University of Michigan, Ann Arbor, USA in 2001 and has been active in the areas such as Markov decision processes, machine learning, maintenance optimization and supply chain management. He has worked closely with private sector including LG Electronics, Nestle, Unilever, Kinross Gold, to name a few. He served as a co-chair of Workshop on Quantitative Finance and Risk Management 2012, and served as a member of the Scientific Committee for the INFORMS MSOM 2015 conference, the 26th International Conference on Flexible Automation and Intelligent Manufacturing 2016.