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Marina Johnson

Assistant Professor, Information Management and Business Analytics

BA, Gazi University
MS, DEU University
PhD, State University of New York at Binghamton
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Dr. Johnson is an Assistant Professor in the Feliciano School of Business at Montclair State University. Dr. Johnson completed her Ph.D. at The State University of New York, Binghamton. During her Ph.D., she focused on machine learning, data mining, and metaheuristic optimization.

Before becoming an academic, Dr. Johnson has worked in various companies in the industry including Hugo Boss, and Comcast - NBC Universal. During her industry experience, she extensively used optimization, simulation, and predictive modeling tools.

Dr. Johnson also held a faculty position at the University of Dayton (UD), where she became the program coordinator of the Quality Management Minor. At the UD, Professor Johnson collaborated with other researchers across the campus on several grants.

Dr. Johnson's research interests lie in the area of applications of machine learning and optimization, ranging from marketing analytics to health informatics.

Using active learning and entrepreneurial mindset learning principles, Dr. Johnson continuously explores educational technology tools to increase student learning outcomes.

Dr. Johnson enjoys traveling, hiking, and doing yoga.


Machine Learning,
Metaheuristic Optimization,
Data Mining,
Data Science,
Business Analytics

Professional Experience

  • Principal Data Scientist/Senior Manager, Comcast - NBC Universal (2017 - 2018)
  • Assistant Professor, The University of Dayton (2015 - 2017)
  • Graduate Research Assistant at United Services Hospital & Graduate School , State University of New York, Binghamton (2010 - 2014)
  • Senior Data Analytics Consultant, Hugo Boss (2007 - 2010)
  • Assistant Professor, Montclair State University (2018 - Present)

Honors & Awards

  • Associate Member, Alpha Pi Mu Honor Society (January 2012)
  • Best Paper Award, Information and Communication Tecnologies in Organizations and Society (ICTO) Conference 2019 (October 2019)

Refereed Published Articles

  • M. Johnson, N. Nagarur, (2015). Multi-stage Methodology to Detect Health Insurance Claim Fraud. Healthcare Management Science
  • M. Johnson, A. Albizri, R. Jain (2020). Exploratory analysis to identify concepts, skills, knowledge, and tools to educate business analytics practitioners. Decision Sciences Journal of Innovative Education
  • M. Johnson, A. Albizri, R. Jain (2020). Exploratory Analysis to Identify Concepts, Skills, Knowledge, & Tools to Educate Business Analytics Practitioners. Decision Sciences Journal of Innovative Education
  • M. Johnson, M. Berenson (2019). Choosing Among Computational Software Tools to Enhance Learning in Introductory Business Statistics. Decision Sciences Journal of Innovative Education (DSJIE)
  • P. Appiah-Kubi, M. Johnson, E. Trappe (2019). Service Learning in Engineering Technology: Do Students Have Preferences on Project Types?. Journal of Engineering Technology
  • M. Johnson, R. Jain, m. Brennan, E. Swartz, D. Silver, J. Paolini, S. Mamonov, C. Hill (2021). Developing Big Data and AI Workforce Roadmap for A Data Driven Economy. Global Institute of Flexible Systems Management
  • S. Simsek, A. Albizri, M. Johnson, T. Custis, S. Weikert (2021). Predictive Data Analytics for Contract Renewals: A Decision Support Tool for Managerial Decision Making. Journal of Enterprise Information Management
  • M. Johnson, A. Albizri, A. Harfouche (2021). Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers
  • A. Johnson, M. Johnson, N. Nagarur (2021). Supply Chain Design Under Disruptions Considering Risk Mitigation Strategies for Robustness and Resiliency. International Journal of Logistics Systems & Management (IJLSM)
  • E. Swartz, P. Brennan-Tonetta, R. Jain, M. Johnson, S. Mamonov, M. Hale, J. Jayaraman (2022). In search of pedagogical approaches to teaching business ethics in the era of digital transformation. Journal of Big Data and Artificial Intelligence
  • R. Jain, M. Johnson, A. Albizri, G. Elias (2022). An Open System Architecture Framework for Interoperability (OSAFI). International Journal of Business Information Systems
  • M. Johnson, R. Jain, M. Brennan-Tonetta, E. Swartz, D. Silver, J. Paolini, S. Mamonov, C. Hill (2021). Impact of Big Data and Artificial Intelligence On Industry: Developing A Workforce Roadmap for a Data Driven Economy. Global Journal of Flexible Systems Management
  • M. Johnson, A. Albizri, S. Simsek (2022). Artificial Intelligence in Healthcare Operations to Enhance Treatment Outcomes: A Framework to Predict Lung Cancer Prognosis for Tailoring of Treatment Strategies. Annals of Operations Research
  • M. Johnson, A. Albizri, A. Harfouche, S. Wamba (2022). Integrating Human Knowledge into Artificial Intelligence for Complex and Ill-Structured Problems: Informed Artificial Intelligence. International Journal of Information Management
  • S. Tutun, A. Tosyali, H. Sangrody, M. Khasawneh, M. Johnson, A. Albizri, A. Harfouche (2022). Artificial Intelligence in Energy Industry: Forecasting Electricity Consumption through Cohort Intelligence & Adaptive Neural Fuzzy Inference System. Journal of Business Analytics
  • M. Johnson, R. Misra, M. Berenson (2022). Integrating Bayesian and Markov Methods in Business Analytics Curricula. Decision Sciences Journal of Innovative Education (DSJIE)
  • 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
  • M. Johnson, R. Malaga (2023). Exploring the relationship between YouTube video optimisation practices and video rankings for online marketing: a machine learning approach. Journal of Business Analytics
  • R. Jain, M. Johnson, A. Albizri, G. Elias (2022). An open system architecture framework for interoperability. International Journal of Business Information Systems
  • S. Tutun, M. Johnson, A. Ahmed, A. Albizri, S. Irgil, I. Yesilkaya, E. Ucar, T. Sengun, A. Harfouche (2022). An AI-based Decision Support System for Predicting Mental Health Disorders. Information Systems Frontiers
  • M. Johnson, A. Albizri, A. Harfouche, S. Tutun (2023). Digital Transformation to Mitigate Emergency Situations: Increasing Opioid Overdose Survival Rates through Explainable AI. Industrial Management & Data Systems
  • S. Tutun, A. Harfouche, A. Albizri, M. Johnson, H. He (2023). A Responsible AI Framework for Mitigating the Ramifications of the Organ Donation Crisis. Information Systems Frontiers
  • Y. Alnsour, M. Johnson, A. Albizri, A. Harfouche (2023). Predicting Patient Length of Stay Using Artificial intelligence to Assist Health Care Professionals in Resource Planning and Scheduling Decisions. Journal of Global Information Management
  • C. Hill, L. Du, M. Johnson, B. McCullough (2024). Comparing Programming Languages for Data Analytics: Accuracy of Estimation in Python and R. Wiley Interdisciplinary Reviews (WIRES): Data Mining and Knowledge Discovery

Published Proceedings

  • M. Johnson, Y. Han, N. Nagarur, (5s). 2013. A Simulation Model for Blood Supply Chain Systems Proceedings of the 2013 Annual Industrial and Systems Engineering Research Conference
  • A. Alazzam, M. Johnson, H. Lewis (5s). 2013. A New Optimization Algorithm for Non-convex Problems Proceedings of the 2013 Industrial and Systems Engineering Research Conference
  • A. Albizri, M. Johnson, R. Jain (5s). 2018. The Future of Business Analytics Education: Closing the Gap between Academia & Industry 2018 DSI Annual Meeting Proceedings
  • M. Johnson, M. Berenson (5s). 2018. Comparing Two Free Software Platforms for Teaching an Introductory Business Statistics Course Decision Science Institute Annual Conference
  • M. Johnson, A. Johnson, N. Nagarur (5s). 2018. Conceptual Framework for Designing Robust and Resilient Supply Chains Decision Sciences Institute Annual Conference
  • E. Swartz, R. Jain, M. Johnson (5s). 2022. Out of Africa: Tracking Women as Digital Entrepreneurs in Africa South of the Sahara Diana International Research Conference