Marina Johnson

Biography

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.

Education

• BA, Gazi University
• MS, DEU University
• PhD, State University of New York at Binghamton

Publications

• Conference Proceedings: A. Alazzam, M. Johnson, H. Lewis (2013). A New Optimization Algorithm for Non-convex Problems. Proceedings of the 2013 Industrial and Systems Engineering Research Conference
• Conference Proceedings: M. Johnson, Y. Han, N. Nagarur, (2013). A Simulation Model for Blood Supply Chain Systems. Proceedings of the 2013 Annual Industrial and Systems Engineering Research Conference
• Journal Article: M. Johnson, N. Nagarur, (2015). Multi-stage Methodology to Detect Health Insurance Claim Fraud. Healthcare Management Science
• Conference Proceedings: A. Albizri, M. Johnson, R. Jain (2018). The Future of Business Analytics Education: Closing the Gap between Academia & Industry. 2018 DSI Annual Meeting Proceedings
• Journal Article: M. Johnson, A. Albizri, S. Simsek (2022). Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis. Annals of Operations Research
• Journal Article: 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)
• Journal Article: 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
• Journal Article: M. Johnson, R. Jain, P. 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
• Conference Proceedings: M. Johnson, A. Johnson, N. Nagarur (2018). Conceptual Framework for Designing Robust and Resilient Supply Chains. Decision Sciences Institute Annual Conference
• Conference Proceedings: M. Johnson, M. Berenson (2018). Comparing Two Free Software Platforms for Teaching an Introductory Business Statistics Course. Decision Science Institute Annual Conference
• Journal Article: P. Appiah-Kubi, M. Johnson, E. Trappe (2019). Service Learning in Engineering Technology: Do Students Have Preferences on Project Types?. Journal of Engineering Technology
• Journal Article: M. Johnson, M. Berenson (2019). Choosing Among Computational Software Tools to Enhance Learning in Introductory Business Statistics. Decision Sciences Journal of Innovative Education (DSJIE)
• Journal Article: 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
• Journal Article: 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
• Journal Article: 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
• Journal Article: 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
• Journal Article: 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
• Journal Article: 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
• Journal Article: 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
• Journal Article: Y. Alnsour, M. Johnson, A. Albizri, A. Harfouche (2023). Predicting Patient Length of Stay Using Artificial Intelligence to Assist Healthcare Professionals in Resource Planning and Scheduling Decisions. Journal of Global Information Management
• Journal Article: M. Johnson, A. Albizri, A. Harfouche, S. Tutun (2023). Digital transformation to mitigate emergency situations: increasing opioid overdose survival rates through explainable artificial intelligence. Industrial Management & Data Systems
• Journal Article: S. Tutun, A. Tosyali, H. Sangrody, M. Khasawneh, M. Johnson, A. Albizri, A. Harfouche (2023). Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence & adaptive neural fuzzy inference system. Journal of Business Analytics
• Journal Article: R. Jain, M. Johnson, A. Albizri, G. Elias (2022). An open system architecture framework for interoperability. International Journal of Business Information Systems
• Journal Article: M. Johnson, R. Misra, M. Berenson (2022). Integrating Bayesian and Markov Methods in Business Analytics Curricula. Decision Sciences Journal of Innovative Education (DSJIE)
• Journal Article: 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
• Conference Proceedings: E. Swartz, R. Jain, M. Johnson (2022). Out of Africa: Tracking Women as Digital Entrepreneurs in Africa South of the Sahara. Diana International Research Conference
• Journal Article: 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
• Journal Article: M. Johnson, A. Albizri, A. Harfouche, S. Fosso-Wamba (2022). Integrating human knowledge into artificial intelligence for complex and ill-structured problems: Informed artificial intelligence. International Journal of Information Management
• Journal Article: M. Johnson, A. Albizri, A. Harfouche (2023). Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers
• Journal Article: 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
• Journal Article: M. Johnson, A. Albizri, A. Harfouche (2023). Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers
• Journal Article: C. Hill, F. Irshaidat, M. Johnson, J. Fresneda (2025). An Analytical Assessment of Sentiment Analysis Trends and Methods Through Systematic Review and Topic Modeling . Elsevier
• Journal Article: C. Hill, L. Du, M. Johnson, B. McCullough (2024). Comparing programming languages for data analytics: Accuracy of estimation in Python and R. WIREs Data Mining and Knowledge Discovery
• Journal Article: D. Zirek, M. Johnson, S. Tutun (). Systematic Literature Review of Smart Contracts in Financial Services. Research in International Business and Finance (RIBAF)

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)