Publications

[20] Xames, M. D., & Topcu, T. G. (2026). Digital engineering transformation as a sociotechnical challenge: Categorization of barriers and their mapping to DoD’s policy goals. Systems Engineering,  e70059.  [DOI]

[19] Xames, M. D., Topcu, T. G., Parker, S. H., Zagarese, V., & Epling, J. (2025). Evaluating CFIR 2.0 in identifying digital twin implementation challenges in healthcare: Bridging the dichotomy between engineering and healthcare communities. Frontiers in Digital Health, 7, 1611225. [DOI]

[18] Xames, M. D., & Topcu, T. G. (2025). How can digital twins support the economic, environmental, and social sustainability of healthcare systems: A systematic review focused on the triple-bottom-line. IEEE Access, 13, 64390-64411. [DOI]

[17] Ahmed, K. A., Humaira, … & Xames, M. D. (2025). Advancing breast cancer prediction: Comparative analysis of ML models and deep learning-based multi-model ensembles on original and synthetic datasets. PLOS One, 20(6), e0326221. [DOI]

[16] Xames, M. D. (2025). Toward a socially sustainable workforce in service operations: Predicting employee burnout with ensemble machine learning. Sustainable Manufacturing and Service Economics, 100033. [DOI]

[15] Paul, S., Liza, S. A., … Xames, M. D., & Rahman, R. (2025). Post-pandemic sustainable supply chain recovery planning: a case study from the automobile industry. Journal of Management Analytics, 12(3), 509–551.  [DOI]

[14] Xames, M. D. & Antezana, R. U. (2025). System dynamics modeling of preventive care strategies for addressing obesity and healthcare expenditures in the United States. Journal of Systems Thinking in Practice, 4(3), 22-41. [DOI]

[13] Xames, M. D., & Topcu, T. G. (2024). A systematic literature review of digital twin research for healthcare systems: Research trends, gaps, and realization challenges. IEEE Access, 12, 4099-4126. [DOI]

[12] Xames, M. D., Torsha, F. K., & Sarwar, F. (2023). A systematic literature review on recent trends of machine learning applications in additive manufacturing. Journal of Intelligent Manufacturing, 34(6), 2529-2555. [DOI]

[11] Xames, M. D., & Shefa, J. (2023). ChatGPT for research and publication: Opportunities and challenges. Journal of Applied Learning and Teaching, 6(1), 390-395. [DOI]

[10] Xames, M. D., Shefa, J., Azrin, F. A., Uddin, A. S. M. N., Habiba, U., & Zaman, W. (2023). A systematic review of modeling approaches in green supply chain optimization. Environmental Science and Pollution Research, 30(53), 113218-113241. [DOI]

[9] Xames, M. D., Shefa, J., Sarwar, F. (2023). Bicycle industry as a post-pandemic green recovery driver in an emerging economy: A SWOT analysis. Environmental Science and Pollution Research, 30(22), 61511-61522. [DOI]

[8] Shefa, J., Xames, M. D., Hasan, A. A., & Talapatra, S. (2023). Feasibility study of common effluent treatment plant for management of industrial wastewater: Case study of Bangladeshi textile industries. Environmental Quality Management, 33(4), 165-178. [DOI]

[7] Mahmud, P., Ahmed, M., Janan, F., Xames, M. D., & Chowdhury, N. R. (2023). Strategies to develop a sustainable and resilient vaccine supply chain in the context of a developing economy. Socio-Economic Planning Sciences, 87, 101616. [DOI]

[6] Roy, A., Islam, M., Karim, M., Ahmed, K. A., Khan, A. R., Uddin, M., & Xames, M. D. (2023). Comparative analysis of KNN and SVM in multicriteria inventory classification using TOPSIS. International Journal of Information Technology, 15(7), 3613-3622. [DOI]

[5] Tonny, F., Maliha, A., Chayan, M., & Xames, M. D. (2023). Optimization of overall equipment effectiveness (OEE) factors: Case study of a vegetable oil manufacturing company. Management Science Letters, 13(2), 124-135. [DOI]

[4] Tonny, F. A., Chayan, M. I., Maliha, A., & Xames, M. D. (2023). Downtime analysis of a vegetable oil manufacturing company: a case study. International Journal of Productivity and Quality Management, 46(3), 287-309. [DOI]

[3] Xames, M. D., Tasnim, F., & Mim, T. I. (2022). COVID-19 and food supply chain disruptions in Bangladesh: Impacts and strategies. International Journal of Research in Industrial Engineering, 11(2), 155-164. [DOI]

[2] Xames. M. D., Torsha, F. K., & Sarwar, F. (2022). ANN-based performance prediction of electrical discharge machining of Ti-13Nb-13Zr alloys. World Journal of Engineering, 21(2), 217-227. [DOI]

[1] Mim, T. I., Tasnim, F., Shamrat, B. A. R., & Xames, M. D. (2022). Performance prediction of green supply chain using Bayesian belief network: Case study of a textile industry. International Journal of Research in Industrial Engineering, 11(4), 327-348. [DOI]

[6] Xames, M. D., Khayal, I.S., & Topcu, T. G. (2026).How Far Are We in Using MBSE for Digital Twins for Human-in-the-Loop Systems? Insights from a Case Study. Conference on Systems Engineering Research (CSER) 2026.

[5]  Xames, M. D., & Topcu, T. G. (2025). A sociotechnical categorization of barriers to digital engineering transformation and their mapping against the DOD’s policy goals. 10th International Engineering Systems Symposium (CESUN) 2025.

[4]  Xames, M. D., & Topcu, T. G. (2025). Stakeholder perspectives on digital twin implementation challenges in healthcare: Insights from a provider digital twin case study. IISE Annual Conference & Expo 2025. [DOI]

[3]  Xames, M. D., & Topcu, T. G. (2024). A rapid review of how model-based systems engineering is used in healthcare systems. INCOSE International Symposium, 34(1), 1447-1462. [DOI]

[2]  Xames, M. D., & Topcu, T. G. (2023). Toward digital twins for human-in-the-loop systems: A framework for workload management and burnout prevention in healthcare systems. In Proceedings of the 3rd Annual IEEE International Conference on Digital Twins and Parallel Intelligence, Orlando, FL, USA, 7-9 November 2023. [DOI]

[1] Sadat, A., Xames, M. D., & Azeem, A. (2017). A multi-objective mathematical optimization approach to a three-echelon green supply chain management subject to disruption at plant. In Proceedings of 1st International Conference on Industrial Engineering and Operations Management (pp. 44-61). [DOI]