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Eyyub Kibis

Assistant Professor, Information Management and Business Analytics, Feliciano School of Business

Office:
Feliciano School of Business 489
Email:
kibise@montclair.edu
Degrees:
BS, Bogazici University
MA, University of Houston
MS, University of Houston
PhD, Wichita State University
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Bio

Dr. Eyyub Kibis is an Assistant Professor at the Feliciano School of Business in the Information Management and Business Analytics (IMBA) department. Prior to teaching at Â鶹´«Ã½ÔÚÏß, he was an Assistant Professor of Business Analytics at the College of Saint Rose in Albany, NY. He is a member of several professional organizations including the Industrial Engineering Honor Society, Alpha Phi Mu, INFORMS, Production and Operations Management (POM), and Decision Sciences Institute (DSI). He is currently the co-chair of the INFORMS Workshop on Data Mining and Decision Analysis.

Research

  • An SIR Model for controlling the novel coronavirus (2019-nCoV) outbreak: Policies and suggestions
  • Capacity Planning of Hospital Beds and Ventilators in New York City during COVID-19
  • An integrated machine learning approach with mixed integer linear programming: Determining optimal chemotherapy dosage for stage II breast cancer patients
  • A tree augmented Bayesian belief approach to predict IPO valuations and the money left on the table

Professional Experience

  • Assistant Professor of Business Analytics, The College of Saint Rose (2017 - 2020)

Consulting

  • Technical/Professional Work, Edgewell Personal Care. (December 2024 - May 2026). The company seeks to eliminate certain items from its sunscreen portfolio. I am developing an optimization model to determine which products—and their associated raw materials—should be discontinued to minimize revenue loss.

Honors & Awards

  • Donald D. Sbarra Endowed Fellowship, Wichita State University (November 2014)
  • Ollie A. & J.O. Heskett Graduate Fellowship, Wichita State University (April 2015)
  • D. W. Hodgson Outstanding Doctoral-level Student Award, Wichita State University (November 2015)
  • Best Graduate Research Award, Wichita State University (April 2016)
  • 2019 INFORMS MIF Best Paper Finalist, 2019, INFORMS (November 2019)
  • The Best Paper Award, 2022 Annual Informs Conference - ENRE Society (October 2022)
  • Poster Presentation Award - Second Place, 2022 INFORMS Business Analytics Conference (April 2022)
  • Harvey J. Greenberg Research Award - Honorable Mention, 2022 Annual Informs Conference - Computing Society (October 2022)

Refereed Published Articles

  • E. Kibis, I. Buyuktahtakin (2017). Optimizing invasive species management: A mixed-integer linear programming approach. European Journal of Operational Research
  • I. Buyuktahtakin, E. Kibis, H. Cobuloglu, G. Houseman, T. Lampe (2015). An age- structured bio-economic model of invasive species management: insights and strategies for optimal control. Biological Invasions
  • S. Simsek, U. Kursuncu, E. Kibis, M. AnisAbdellatif, A. Dag (2020). A hybrid data mining approach for identifying the temporal effects of variables associated with breast cancer survival. Expert Systems with Applications
  • E. Kibis, I. Buyuktahtakin (2019). Optimizing multi-modal cancer treatment under 3D spatio-temporal tumor growth. Mathematical Biosciences
  • S. Simsek, U. Kursuncu, E. Kibis, A. Dag (2018). A Machine Learning-Based Holistic Approach to Predict the Survival of Breast Cancer Patients. International Journal of Electrical, Electronics and Data Communication
  • I. Buyuktahtakm, E. des-Bordes, E. Kibis (2018). A new epidemics-logistics model: Insights into controlling the Ebola virus disease in West Africa. European Journal of Operational Research
  • A. Asilkalkan, A. Dag, S. Simsek, O. Aydas, E. Kibis, D. Delen (2025). Streamlining patients’ opioid prescription dosage: an explanatory bayesian model. Annals of Operations Research
  • S. Simsek, A. Dag, K. Coussement, E. Kibis, S. Ragothaman, A. Asilkalkan (2025). A decision support framework for misstatement identification in financial reporting: A hybrid tree-augmented Bayesian belief approach. Decision Support Systems
  • O. Cosgun, M. Rivero, B. Cankaya, E. Kibis (2024). Water Quality Index Prediction using Machine Learning and XAI techniques in San Joaquin Valley Region. International Journal of Information and Decision Sciences
  • B. Cankaya, B. Erenay, E. Kibis, A. Glassman, D. Delen (2024). Charting the future of pilots: maximizing airline workforce efficiency through advanced analytics. Operational Research
  • B. Akcam, E. Kibis, Z. Akcam Kibis (2024). Analyzing the Initial Reactions to National Association of Realtors Settlement on Broker Commissions in 2024. Journal of Real Estate Practice and Education
  • A. Dag, M. Johnson, E. Kibis, S. Simsek, B. Cankaya, D. Delen (2023). A machine learning decision support system for determining the primary factors impacting cancer survival and their temporal effect. Healthcare Analytics
  • A. Dag, Z. Akcam, E. Kibis, S. Simsek, D. Delen (2022). A probabilistic data analytics methodology based on Bayesian Belief network for predicting and understanding breast cancer survival. Knowledge-Based Systems
  • H. Dolatsara, E. Kibis, M. Caglar, S. Simsek, A. Dag, G. Dolatsara, D. Delen (2022). An Interpretable Decision-Support Systems for Daily Cryptocurrency Trading. Expert Systems with Applications
  • E. Kibis, I. Buyuktahtakin, R. Haight, N. Akhundov, K. Knight, C. Flower (2020). A new multi-stage stochastic programming model and cutting planes for the optimal surveillance and control of emerald ash borer in cities. INFORMS Journal on Computing

Published Proceedings

  • E. Kibis, E. Buyuktahtakin (5s). 2017. Data analytics approaches for breast cancer survivability: Comparison of data mining methods IIE Annual Conference