博彩平台

主题: data driven research in supply chain and service operations.

时间：2017年4月12日13:30

地点：财科馆三楼小型学术报告厅

报告人: Dr. Chung-Piaw Teo

摘要: There has been a surge of interest in data science and its application in operations management. The key question here is how traditional approach to modelling OM issues can be enhanced with more refined and real time data, and how to develop a new science for data driven research for the OM community. This talk reviews a few recent cases, and sketches a few directions that hopefully will be useful for junior researchers in this area. The key message is that OM scholars must embrace the advances in modern machine learning literature to develop data driven models for OM questions.

报告人简介: Dr. Chung-Piaw Teo is a Provost Chair Professor of Decision Sciences at the NUS Business School. Prior to his current appointments, he was Acting Deputy Dean, Vice-Dean of the Research & PhD Program as well as Head of the Decision Sciences Department in the School. He was an Eschbach Scholar in Northwestern University (US), Professor in Sungkyunkwan Graduate School of Business (Korea), and a Distinguished Visiting Professor in YuanZe University (Taiwan). His research interests lie in service and manufacturing flexibility, discrete optimization, ports container operations, matching and exchange, and healthcare. He is currently an area editor for OR (Operations and Supply Chains), and associate editor of Management Science (Optimization). He has also served on several international committee such as the Chair of the Nicholson Paper Competition (INFORMS, US), member of the IMPACT Prize Committee (INFORMS, US), Lanchaster Prize Committee (INFORMS, US), Fudan Prize Committee on Outstanding Contribution to Management (China), and the Hong Kong PhD Fellowship Scheme Selection Panel.