バイオ

Sridhar Seshadri obtained his Ph.D. at the University of California, Berkeley after graduating from the Indian Institute of Technology, Madras, India and the Indian Institute of Management, Ahmedabad, India. He is currently the Alan J and Joyce D Baltz Professor in the Geis College of Business. He is the Area Chair for the Information, Operations Management, Supply Chain and Analytics area in the Business Administration Department. Previously, he had served as the Deputy Dean (Operations) and Area Leader Operations Management at the Indian School of Business. He has been a faculty member at The McCombs School of Business at the University of Texas at Austin, the Stern School of Business at New York University and the Administrative Staff College of India. During his teaching career, he was awarded the Stern School of Business Teaching Excellence Award and recognized as the Stern School of Business Undergraduate Teacher of the Year. His current research projects focus on pricing and revenue optimization for the Media industry, development of Micro, Small and Medium manufacturing enterprises in India, pricing and crop choice for agricultural supply chains in India, and sourcing and risk management in global supply networks. In addition, he serves on the board of directors for Nomi Networks and is on the advisory board of Wiley Innovation Advisory Council on Analytics. His professional service includes serving as the Associate Editor, Naval Research Logistics; Associate Editor, Management Science, Area Editor, Operations Research Letters; and Department Editor (Operations and Finance Interface), Production and Operations Management Journal. He has co-authored the book Toyota's Supply Chain Management: A Strategic Approach to Toyota's Renowned System and edited the volume Managing Supply Chains on the Silk Road. His current book project is Essentials of Business Analytics: An Introduction to its Methodology and Applications, to be published by Springer in April 2019.

コース

Predictive Analytics and Data Mining

Data Modeling and Regression Analysis in Business