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1. U Mohammad and S Sorour, “Dynamic Task Allocation for Mobile Edge Learning”, submitted to the IEEE Transactions on Parallel and Distributed Systems.
2. F Madkour, U Mohammad, S Sorour, M Hefeida and A Abdel-Rahim, “A Vendor-Independent Reliability Testing Model for Vehicle-to-Infrastructure Communications”, accepted for presentation at the Transportation Research Board (TRB) Meetings, 2020.
3. U Baroudi, M Bin-Yahya, M Alshammari and U Yaqub, “Ticket-based QoS routing optimization using genetic algorithm for WSN applications in smart grid”, Journal of Ambient Intelligence and Humanized Computing, vol. 10, no. 4, pp. 1325-1338, 2019.
   • URL: https://link.springer.com/article/10.1007/s12652-018-0906-0
   • DOI: 10.1007/s12652-018-0906-0
4. U Yaqub, A Al-Nasser and T Sheltami, “Implementation of a hybrid wind-solar desalination plant from an Internet of Things (IoT) perspective on a network simulation tool”, Applied Computing and Informatics, vol. 15, no. 1, pp. 7-11, 2019.
   • URL: https://www.sciencedirect.com/science/article/pii/S221083271730354X
   • DOI: 10.1016/j.aci.2018.03.001

1. Umair Mohammad, Sameh Sorour and Mohamed Hefeida, “Task Allocation for Federated Mobile Edge Learning with Delay and Energy Constraints”, submitted to the 6^th IEEE World Forum on IoT.
2. Umair Mohammad and Sameh Sorour, “Adaptive Task Allocation for Mobile Edge Learning”, published in proceedings of the 2019 IEEE Wireless Communications and Networking Conference Workshops (IEEE WCNCW 2019, Marrakech, Morocco).
   • URL: https://ieeexplore.ieee.org/document/8902527
   • DOI: 10.1109/WCNCW.2019.8902527
3. Umair Mohammad and Sameh Sorour, “Multi-Objective Resource Optimization for Hierarchical Mobile Edge Computing”, published in proceedings of the 2018 IEEE Global Communications Conference: Mobile and Wireless Networks (Globecom2018 MWN).
   • URL: https://ieeexplore.ieee.org/document/8648109
   • DOI: 10.1109/GLOCOM.2018.8648109
4. Mohammad Umair Yaqub and Mohammad Saad Al-Ahmadi, “Application of Combined ARMA-Neural Network Models to Predict Stock Prices”, published in proceedings of the 3rd Multidisciplinary International Social Networks Conference on Social Informatics (Data Science, 2016), New Jersey, 2016.
   • URL: https://dl.acm.org/citation.cfm?id=2955171
   • DOI: 10.1145/2955129.2955171