Ilbin Lee is an Assistant Professor in Accounting, Operations and Information Systems at the Alberta School of Business. Dr. Lee joined the research team of Health Analytics at Georgia Tech after finishing his Ph.D. in Industrial and Operations Engineering at the University of Michigan. During Ph.D., he had developed solution algorithms for sequential decision-making problems under uncertainty and established theoretical properties of the problems and the solution methods. In 2013 and 2014, he worked as a research intern at IBM T.J. Watson Research Center, working on decision-making problems involving large-scale data analysis for treatment planning in intensive care units. Before Ph.D., he worked as a software engineer at Electronics and Telecommunications Research Institute in South Korea from 2007 to 2010, working on speech recognition and more broadly, machine learning. He holds a M.S. in Applied Mathematics and Statistics from SUNY at Stony Brook and a B.S. in Mathematics from KAIST.
Dr. Lee is interested in health data analytics and large-scale optimization problems arising in data analytics. He is applying his expertise in operations research and machine learning to translating large-scale health data into recommendations for policy makers and to develop novel approaches for solving optimization problems in healthcare applications.