N. Orkun Baycik

Clinical Assistant Professor, Markets, Public Policy, and Law

I am a Clinical Assistant Professor in the Questrom School of Business at Boston University (BU). Before joining BU in July 2022, I was an Assistant Professor of Quantitative Methods and Supply Chain Management in the School of Business at Shenandoah University (SU). I received my PhD in Industrial and Systems Engineering at Rensselaer Polytechnic Institute (2018) and my MSc in Industrial Engineering at the University of Arkansas (2014).

My research focuses on machine learning and prescriptive analytics methods with applications in modeling and disrupting illegal supply networks; digital transformation in operations and supply chain management, network interdiction, and data analytics in the nonprofit sector.

My teaching interests and background are in the field of analytics, optimization, and operations & supply chain management. At BU, I teach QM 880 Business Analytics: Spreadsheet Optimization and Simulation, BA 472 Business Experiments and Causal Methods, and QM 323 Analytics. At SU, I taught courses in Data Analysis for Business and Quantitative Methods at the undergraduate level, and Business Analytics and Operations & Supply Chain Management at the graduate level.

    Education
  • PhD, Rensselaer Polytechnic Institute, 2018
  • MS, University of Arkansas, 2014
    Publications
  • Baycik, N., Gowda, S. (In Press). "Digitalization of Operations and Supply Chains: Insights from Survey and Case Studies", Digital Transformation and Society
  • Orkun Baycik, N. (2022). "Machine learning based approaches to solve the maximum flow network interdiction problem", Computers & Industrial Engineering, 167 107873-107873
  • Baycik, N., Sharkey, T., Rainwater, C. (2020). "A Markov Decision Process approach for balancing intelligence and interdiction operations in city-level drug trafficking enforcement", Socio-Economic Planning Sciences, 69 100700-100700
  • Baycik, N., Sullivan, K. (2019). "Robust location of hidden interdictions on a shortest path network", IISE Transactions, 51 (12), 1332-1347
  • Baycik, N., Sharkey, T. (2019). "Interdiction-Based Approaches to Identify Damage in Disrupted Critical Infrastructures with Dependencies", Journal of Infrastructure Systems, 25 (2)
  • Bahulkar, A., Baycik, N., Sharkey, T., Shen, Y., Szymanski, B., Wallace, W. (2018). "Integrative Analytics for Detecting and Disrupting Transnational Interdependent Criminal Smuggling, Money, and Money-Laundering Networks", 2018 IEEE International Symposium on Technologies for Homeland Security (HST)
  • Bahulkar, A., Szymanski, B., Baycik, N., Sharkey, T. (2018). "Community detection with edge augmentation in criminal networks", 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
  • Baycik, N., Sharkey, T., Rainwater, C. (2018). "Interdicting layered physical and information flow networks", IISE Transactions, 50 (4), 316-331
    Research Presentations
  • Baycik, N. Evaluating the Impact of Increased Supply Chain Visibility, Decision Sciences Institute Conference, 2023
  • Baycik, N. Classification Methods for Decision Making in Illegal Drug Trafficking Networks, INFORMS Annual Meeting, Phoenix, 2023
  • Baycik, N. Reinventing Supply Chains through Digital Transformation, Production and Operations Management Society (POMS), 2023
  • Bernadine, D. , Baycik, N. Using Data Analytics to Shift Nonprofit Organizations from Serving to Solving., Southern Management Association Conference, 2021