Assistant professor with solid background in machine learning and artificial intelligence. Mentoring undergraduate and postgraduate students. Interested in research collaborations, especially, multidisciplinary ones.
Programming: Python, C, Java, Matlab, C# and
1. Elreedy, D., Atiya, A.F. and Shaheen, S.I., 2021. Novel pricing strategies for revenue maximization and demand learning using an exploration–exploitation framework. Soft Computing, 25(17), pp.11711-11733.
2. Elreedy, D., Atiya, A.F. and Shaheen, S.I., 2021. Multi-step look-ahead optimization methods for dynamic pricing with demand learning. IEEE Access, 9, pp.88478-88497.
3. Elreedy, D. and Atiya, A.F., 2019. A comprehensive analysis of synthetic minority oversampling technique (SMOTE) for handling class imbalance. Information Sciences, 505, pp.32-64.
4. Elreedy, D., F. Atiya, A. and I. Shaheen, S., 2019. A novel active learning regression framework for balancing the exploration-exploitation trade-off. Entropy, 21(7), p.651.
5. Elreedy, D. and Atiya, A.F., 2019, June. A novel distribution analysis for smote oversampling method in handling class imbalance. In International Conference on Computational Science (pp. 236-248). Springer, Cham.
6. Elreedy, D., Atiya, A.F., Fayed, H. and Saleh, M., 2018. A framework for an agent-based dynamic pricing for broadband wireless price rate plans. Journal of Simulation.
7. El-Reedy, D.A., Atiya, A.F., Fayed, H.A. and Saleh, M., 2014, December. Optimized static pricing approach for revenue maximization in telecommunications. In 2014 10th International Computer Engineering Conference (ICENCO) (pp. 57-60). IEEE.
8. Elreedy D, Atiya, A.F. and Fayed, H, 2015, Agent-Based Dynamic Pricing for Wireless Services, a Poster paper presented by me in NetMob15 Organized by MIT Media Lab.
9. Ibrahim, M.N., Mahmoud, M.N. and El-Reedy, D.A., 2016. Bel-Arabi: advanced Arabic grammar analyzer. International Journal of Social Science and Humanity, 6(5), p.341.
Advances in Mathematical Physics.