Mahmoud Ashraf

I am a PhD student in Industrial Engineering at the University of Pittsburgh, where I work with Dr. Lamperski and Prof. Prokopyev on Adaptive Bilevel Optimization and its applications to decision science. I have a Master of Science in Industrial Engineering and Systems Management from the Egypt-Japan University of Science and Technology, which I obtained in 2023 after joining the institution as a Research Scholar in 2021. Before that, I was a Teaching Assistant at Alexandria University, where I also earned my Bachelor of Science in Production Engineering in 2017. My research interests include Supply Chain Management and Resilience, Blockchain, Digital Twin, Machine Learning, Operations Research, and Decision Science.

  • MSc, Industrial Engineering and Systems Management, Egypt-Japan University of Science and Technology, 2021 - 2023
  • BSc, Production Engineering, Alexandria University, 2012 - 2017
  • PhD, Industrial Engineering, University of Pittsburgh, 2023 - present

  • Ashraf, M., Ali, I., & Eltawil, A. (2026). A hybrid deep learning-based approach for disruption detection and recovery planning in a prototype cognitive digital supply chain twin. EXPERT SYSTEMS WITH APPLICATIONS, 297.Elsevier. doi: 10.1016/j.eswa.2025.129531.
  • Ashraf, M., Eltawil, A., & Ali, I. (2024). Disruption detection for a cognitive digital supply chain twin using hybrid deep learning. OPERATIONAL RESEARCH, 24(2).Springer Nature. doi: 10.1007/s12351-024-00831-y.
  • Ashraf, M., Eltawil, A., & Ali, I. (2023). Disruption Detection for a Cognitive Digital Supply Chain Twin Using Hybrid Deep Learning. doi: 10.48550/arXiv.2309.14557.
  • Ashraf, M., & Ali, I. (2022). Evaluation of project completion time prediction accuracy in a disrupted blockchain-enabled project-based supply chain. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS, 10(1).Taylor & Francis. doi: 10.1080/23302674.2022.2152296.
  • Ashraf, M., Eltawil, A., & Ali, I. (2022). Time-To-Recovery Prediction in a Disrupted Three-Echelon Supply Chain Using LSTM*. IFAC-PapersOnLine, 55(10), 1319-1324.Elsevier. doi: 10.1016/j.ifacol.2022.09.573.

  • Ashraf, M., Eltawil, A., & Ali, I. (2023). Cognitive Digital Twins for Supply Chain Resilience Enhancement. INFORMS Annual Meeting 2023.Phoenix, Arizona, United States of America.
  • Ashraf, M., Eltawil, A., & Ali, I. (2022). Time-To-Recovery Prediction in a Disrupted Three-Echelon Supply Chain Using LSTM. 10th IFAC Conference on Manufacturing Modelling Management and Control.Nantes, France. doi: 10.1016/j.ifacol.2022.09.573.
Research Interests
Applied mathematics
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