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Dr. Mamunur Rahman is an Assistant Professor of Decision Sciences in the College of Business at Coppin State University. His research integrates data-driven decision-making, machine learning, agent-based modeling, and computer simulation to address complex business and societal challenges across healthcare, supply chain, transportation systems, and organizational operations.
Dr. Rahman served as a key contributor to the Deep Dive Assessment Report on the Electric Grid and High Voltage Direct Current Supply Chain (HVDC SC), prepared for the U.S. Department of Energy’s Office of Electricity and Advanced Manufacturing Office. This work supported the implementation of President Biden’s Executive Order 14017 on strengthening America’s supply chains and highlights his expertise in applied analytics, policy-relevant research, and large-scale system assessment.
He has published extensively in leading journals and international conferences in his field, including contributions to two book chapters. His research has been recognized with multiple honors, including the Best Paper Award at the Institute of Industrial and Systems Engineers (IISE) Annual Conference (2019) and a Best Paper Finalist distinction at the Computational Social Science Society of the Americas Annual Conference (2018).
Complementing his academic background, Dr. Rahman brings substantial industry experience from roles in supply chain and manufacturing analytics at Fortune 500 companies. He has also led the development of advanced decision-support software tools, including the Comprehensive Manufacturing Assessment Tool (CMAT) and PyEmission, during his tenure at Idaho National Laboratory.
- Rahman, MM, Jahan, J., Iqbal, G. M. D., & Hossain, M. J. “Evaluating CO₂ Emissions in Urban Traffic from Light-Duty Vehicles: A Comparative Study of Dhaka City and International Driving Cycles”. In: IISE Annual Conference. The Institute of Industrial and Systems Engineers; 2025.
- Rahman MM, Nguyen R, Severson M, Williams S, Hartley D. “A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic.” Decision Analytics Journal; Elsevier; 2023.
- Rahman MM, Nguyen R, Hartley D, Williams S. “A Logistics Planning Tool for E-Waste Collection: Streamlining Sustainability and Efficiency” In: Proceedings of the 8th North American International Conference on Industrial Engineering and Operations Management, Houston, Texas, USA; 2023.
- Rahman MM, Nguyen R, Lu L. “Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach.” Agricultural Systems, Elsevier; 2022.
- Nguyen RT, Severson M, Zhang B, Vaagensmith B, Rahman MM, Toba AL, Price P, Ryan D, Williams S “Electric Grid Supply Chain Review: Large Power Transformers and High Voltage Direct Current Systems.” U.S. Department of Energy; 2022.
- Rahman MM, Hartley DS, Nguyen RT “Self-Configuring Digital Twin for Optimizing E-Waste Recycling.” Idaho National Laboratory; 2022.
- Rahman MM, Zhou Y, Rogers J, Chen V, Sattler M, Hyun K. “A Comparative Assessment of Environmental Emissions Between Gasoline and Electric Vehicles: A Well-To-Wheel Perspective.” Journal of Cleaner Production, Elsevier; 2021.
- Rahman MM, Ghasemi Y, Suley E, Zhou Y, Wang S, Rogers J. “Machine Learning Based Computer Aided Diagnosis of Breast Cancer Utilizing Anthropometric and Clinical Features.” Innovation and Research in Biomedical Engineering, Elsevier; 2021.
- Lu L, Nguyen R, Rahman MM, Winfree J. “Demand Shocks and Supply Chain Resilience: An Agent-Based Modelling Approach and Application to the Potato Supply Chain.” In: Risks in Agricultural Supply Chains. National Bureau of Economic Research, Inc; 2021.
- Rahman MM, Galvez M, Zhou Y. “Evaluation of ‘Crowd-informing’ on Parking Performance and Environmental Emissions: An Agent-Based Simulation of an Urban University Campus.” In: IISE Annual Conference. The Institute of Industrial and Systems Engineers; 2021.
- Ho AF, Zhou Y, Kirby JJ, Rahman MM, Tessitore K, Abdel-Raziq Y, et al. “Causal Effect Analysis of Demographic Concordance on Patient Perception of Physician Trust and Respect in an Emergency Care Setting.” Open Access Emergency Medicine; 2021.
- Rahman MM, Zhou Y, Wang S, Rogers J. “Wart Treatment Decision Support Using Support Vector Machines.” International Journal of Intelligent Systems and Applications. 2020;12(1):1-11.
- Rahman MM, Jahan J, Zhou Y. “Alleviating Traffic Congestion by the Strategy of Modal Shift from Private Cars to Public Transports: A Case of Dhaka City, Bangladesh.” CSSSA 2018, Springer Proceedings in Complexity, Springer; 2020, p. 101–15.
- Rahman MM, Zhou Y, Rogers J. “Performance Evaluation of Median U-Turn Intersection for Alleviating Traffic Congestion: An Agent-Based Simulation Study.” In: IISE Annual Conference. Orlando, FL: The Institute of Industrial and Systems Engineers; 2019.
- Rahman MM, Zhou Y. “Effectiveness of Public Buses to Mitigate Traffic Congestion in Dhaka City: An Agent Based Simulation Study.” In: IISE Annual Conference. Orlando, FL: Institute of Industrial and Systems Engineers; 2018.
- Rahman MM, Wang S, Zhou Y, Rogers J. “Predicting the Performance of Cryotherapy for Wart Treatment Using Machine Learning Algorithms.” In: IISE Annual Conference. Orlando, FL: The Institute of Industrial and Systems Engineers; 2019.
- Robinson RD., Dib ., Mclarty D, Shaikh ., Cheeti R, Zhou Y, Ghasemi Y, Rahman MM, Schrader CD, Wang H. “Productivity, efficiency, and overall performance comparisons between attendings working solo versus attendings working with r
Ph.D. in Industrial Engineering, University of Texas - Arlington, 2020.
Data-driven decision-making, machine learning, agent-based modeling, and computer simulation to address complex business and societal challenges across healthcare, supply chain, transportation systems, and organizational operations.
- Principal Investigator, State of Wisconsin–sponsored Dairy Innovation Hub project, “Precision Livestock Farming: Leveraging Data and Machine Learning to Enhance Dairy Calf Health and Welfare,” $50,000.
- Faculty Mentor, Summer Undergraduate Scholars Program, “Assessing the Environmental Impact of Electric Vehicle Adoption Amid Shifting U.S. Energy Policies,” (Summer 2025).
- Co-Principal Investigator, “Optimizing Dairy Farm Productivity: Predicting Milk Yield and Quality Using Machine Learning on Milking Robot Data,” (Fall 2025).
- Principal Investigator, “Predicting Soybean Yield and Key Drivers Using Machine Learning,” (Spring 2025)
- Exceptional Innovation Contribution Award, Idaho National Laboratory, 2021, for development of the PyEmission Python library.
- Exceptional Innovation Contribution Award, Idaho National Laboratory, 2022, for development of the Comprehensive Manufacturing Assessment Tool (CMAT).
- Best Paper Award, Institute of Industrial and Systems Engineers (IISE) Annual Conference, 2019.
- Best Paper Finalist, Computational Social Science Society of the Americas Annual Conference, 2018.
- Ph.D. Dissertation Fellowship, College of Engineering, University of Texas at Arlington, 2020.
- Lawrence W. Stephens Endowed Scholarship, University of Texas at Arlington, 2020.
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