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.