Dr Masoud graduated with a PhD with a nomination for an outstanding thesis in 2012 in Operations Research and Mathematical Sciences from the School of Mathematical Sciences, Queensland University of Technology (QUT), Australia. He received the M.Phil. Degree in applied mathematics–operations research and decision support systems (2004), and B.SC. With honors in Mathematics and Computers (1998) from Cairo University (CU). Masoud has made significant contributions to mathematical sciences, artificial intelligence, and optimisation as fields of research and practice. Dr Masoud has comprehensive experience and 15 years of work experience in several industrial projects. He has led the optimization, artificial intelligence, and mathematical modelling for signature industrial projects in Australia and Internationally. Based on this experience, Dr Masoud Published more than 70 international journal and conference papers in operations research, artificial intelligence, machine learning, intelligence transport system, and supply chain management.  Furthermore, He constructed industrial linkages with professional domestic and international industrial and governmental associations. For instances:

• Cooperative and Highly Automated Driving (CHAD) (2018-2023)
• Connected/automated vehicles workshops to share knowledge with Saudi Universities (2021/2022)
• AWS Deeprace applications in STEM 2020, 2021
• Glare on tunnel endpoints: Road safety problem, a new methodological approach for analyses and simulations (2019/2020).
• Crash/near-crash detection using machine learning based on the Australian Naturalistic Driving 2019/2020
• Vulnerable Road Users Detection Using Smartphone Sensors & Deep learning (2019/2020)
• Agent-Based Simulation for Automated Vehicle and Pedestrian Interaction at intersections 2020/2021
• Digital Biomass and Beef Optimization 2017- 2018
• Australian Biomass for Bio-energy 06/2016- 08/2016
• Real-time harvest and transport system 10/2014 -10/2016
• Reducing Transport Costs Through the Automation of Schedule Generation 02/2009-03/2012

Internationally,

• Mining Scheduling Methodology in China 2018-2021
• Maximising Green Transportation System Performance with Minimized Environmental Impact During Pandemics: Real Case Study, Qassim University 2022
• Rideshare and portable stations. It was collaborative research with Virginia Tech Transportation Institute, USA, in collaborative research in rideshare and portable stations.

Along with Masoud’s extensive work in research and project delivery, Dr Masoud has an extensive experience for more than tweleve  years in teaching many courses for undergraduate and postgraduate students utilising face-to-face instruction and online technologies to ensure a high level of flexibility for the diverse learning needs of students. 

Dr Masoud Participated in supervising PhD, Masters, Graduate research students, Queensland university of Technology. Dr Masoud has a membership in many professional and academic organizations such as ASOR (Australian society of operations research) and collaborated with many international organizations such as Amazon.

PhD – Operations Research and Mathematical Sciences- Queensland University of Technology, Australia, 2012.

M.SC.  in Operations Research and Decision Support Systems, Cairo University, 2004

B.SC. in Mathematics and Computers, Cairo Univerty, 1998.

Operations Research

Mathematical Sciences

Artificial Intellgence and Machine Learning

Data Science

Optimization

1. Masoud, M., Elhenawy, M., Liu, S. Q., Almannaa, M., Glaser, S., & Alhajyaseen, W. (2023). A Simulated Annealing for Optimizing Assignment of E-Scooters to Freelance Chargers. Sustainability, 15(3), 1869.
2. Masoud, M., Hsieh, J., Helmstedt, K., McGree, J., & Corry, P. (2023). An integrated pasture biomass and beef cattle liveweight predictive model under weather forecast uncertainty: An application to Northern Australia. Food and Energy Security Journal, DOI: 10.1002/fes3.453.
3. Komol,M., Elhenawy, M., Masoud, M., Glaser, S.,Rakotonirainy, A., & Wood, M.,  (2023). Deep RNN based Prediction of Driver’s Intended Movements at Intersection using Cooperative Awareness Messages. IEEE Transactions on Intelligent Transportation Systems, Accepted.
4. Elhenawy, M., Larue, G. S., Masoud, M., Rakotonirainy, A., & Haworth, N. (2023). Using random forest to test if two-wheeler experience affects driver behaviour when interacting with two-wheelers. Transportation research part F: traffic psychology and behaviour, 92, 301-316.
5. Liu, S. Q., Kozan, E., Masoud, M., Li, D., & Luo, K. (2022). Multi-stage mine production timetabling with optimising the sizes of mining operations: an application of parallel-machine flow shop scheduling with lot streaming. Annals of Operations Research, 1-27.
6. SQ Liu, E Kozan, P Corry, M Masoud, & K Luo. (2022).A real-world mine excavators timetabling methodology in open-pit mining. Optimization and Engineering, 10.1007/s11081-022-09741-4.
7. Pinnow, J., Masoud, Mahmoud, Elhenawy, M, & Glaser, S. (2021).A review of naturalistic driving study surrogates and surrogate indicator viability within the context of different road geometries. Accident Analysis and Prevention, 157, Article number: 106185.
8. Zeng, L., Liu, S. Q., Kozan, E., Corry, P., & Masoud, M. (2021). A comprehensive interdisciplinary review of mine supply chain management. Resources Policy, 74, 102274.
9. Masoud, M., Elhenawy, M., Almannaa, M. H., Liu, S. Q., Glaser, S., &Rakotonirainy, A. (2019). Heuristic approaches to solve e-scooter assignment problem. IEEE Access, 7, 175093-175105.