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Eyyub Kibis

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

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

  • A tree augmented Bayesian belief approach to predict IPO valuations and the money left on the table
  • An integrated machine learning approach with mixed integer linear programming: Determining optimal chemotherapy dosage for stage II breast cancer patients
  • 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

Professional Experience

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

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)
  • 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)
  • The Best Paper Award, 2022 Annual Informs Conference - ENRE 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
  • 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
  • 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. Erenay, E. Kibis, B. Cankaya, O. Cosgun (2024). Navigating airline disruptions with strategic pilot planning: an optimization approach for long-term workforce efficiency and service quality. Journal of Marketing Analytics
  • 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. Asilkalkan, A. Dag, S. Simsek, O. Aydas, E. Kibis, D. Delen (2023). Streamlining patients’ opioid prescription dosage: an explanatory bayesian model. Annals of Operations Research
  • 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
  • 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

Published Proceedings

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