headshot of Mahmoud Ashraf

Mahmoud Ashraf

Researcher Graduate Student
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overview

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.

about

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., Eltawil, A., & Ali, I. (2024). Disruption detection for a cognitive digital supply chain twin using hybrid deep learning. OPERATIONAL RESEARCH, 24(2), 23.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), 2152296.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.