Cagri Haksoz

• Ph.D., Operations Management, New York University, 2004
• MPhil, Operations Management, New York University, 2003
• B.S., Industrial Engineering, Bilkent University, 1999

• Teaching Professor, Business Administration, University of Illinois at Urbana-Champaign, 2023 to present
• Visiting Professor of Supply Chain and Operations Management, Indian School of Business, Hyderabad, 2022-2022
• Associate Professor of Operations, Decision, Risk Management, Business School, Durham University, UK, 2019-2023
• MBA Technology Pathway Leader, Business School, Durham University, UK, 2019-2022
• Visiting Associate Professor of Business Analytics, Krannert School of Management, Purdue University, 2018-2019
• Supply Chain Analytics Consultant, Krannert School of Management, Purdue University, 2018-2018
• Visiting Associate Professor of Operations and Supply Chain Management, Indian School of Business, Hyderabad, 2017-2018
• PhD Program Coordinator in Supply Chain/Logistics/Operations, Sabanci University, Turkey, 2015-2016
• Visiting Research Scientist, Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, 2015-2015
• Visiting Scholar, Stern School of Business, Department of Information, Operations, and Management Sciences, New York University, 2013-2013
• Visiting Non-Resident Research Fellow, Regent’s Centre for Transnational Studies, Regent's College, UK, 2012-2015
• Honorary Visiting Fellow, Cass Business School, City University of London, 2008-2011
• Assistant Professor of Supply Chain, Risk, Operations Management, School of Management, Sabanci University, Turkey, 2007-2018
• Adjunct Professor of Operations Management, New York University, London Campus, 2005-2007
• Assistant Professor of Operations Management, Cass Business School, City University of London, 2004-2007
• Operations Consultant, Dut International, Tashkent, Uzbekistan, 1997-1997

• Simsek, K., Haksoz, C., & Cakanyildirim, M. (2019). Managing Supply Chain Risk Through Take-or-Pay Gas Contracts in the Presence of Buyer’s Storage Facilities. The Journal of Energy Markets, 12 (3), 49-73.  link >

Supply Chain Strategy and Management, Data Science and Business Analytics, Service Operations, Strategic Decision Making, Risk Intelligence, Decision Models

Risk Intelligence, Risk Intelligent Leadership, Decision Making, Supply Chain Fragility and Resilience, Data/Business Analytics, Silk Road Supply Chains, Behavioral Science, Complex Adaptive Systems, Arts and Management, Philosophy of Management

• Business Analytics II (BADM 211) Builds on the foundation from the Business Analytics I (BADM 210), synthesizes concepts through hands-on application and project-based learning. Focuses on data acquisition, organization, analysis and visualization in a business setting. Expanding on the use of statistics in generating basic inferences to predictive modeling Identify opportunities for improving business decisions using data, conduct relevant analysis of the gathered and cleaned data, and finally, interpret and present analysis outcomes to decision makers. Using statistical tools and software applications to identify business problems, acquire relevant data, and generate analytic solutions using advanced analytics techniques and tools for generating insights. Introduces the students to analyzing, learning, and prediction using advanced analytics techniques and tools for generating business insights. This course will provide a practical introduction to various techniques regarding clustering, text mining, classification and decision trees, and time series analysis. Finally, the course will introduce advanced and emerging topics in predictive analytics.

• Purchasing and Supply Mgmnt (BADM 324) Examines the analysis, planning, and forms of organization that are associated with the buying functions in business. Major focus on the principal issues involved in the procurement of raw materials, components, equipment, operating supplies, and services. Also treats the unique aspects of institutional and government purchasing. Case problems constitute a major vehicle of instruction.