Aymen Hamrouni is a graduate student within the CEMSE departement pursuing a master's in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST). 

Education and Early Career

Aymen received the 'Diplome d'Ingenieur' degree (summa cum laude) in telecommunication engineering from the Ecole Superieure des Communications de Tunis (SUP'COM), Tunis, Tunisia, in 2019. In 2019, he worked as a research assistant at Stevens Institute of Technology, Hoboken, NJ, USA. In 2020, he was a Research Scholar with the School of Systems and Enterprises, Stevens Institute of Technology. His research interests include the intersection of deep learning for visual computing, applied machine learning, optimization, mathematical modeling, graph theory, and the Internet-of-Things.

Selected Publications

9. A. Hamrouni, T. Alelyani, H. Ghazzai, and Y. Massoud, “Toward Collaborative Mobile Crowdsourcing“, IEEE Internet of Things Magazine, July 2021.
10. A. Hamrouni, H. Ghazzai, T. Alelyani, and Y. Massoud, “Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks“, IEEE Internet of Things Journal, June 2021.
11. A. Hamrouni, H. Ghazzai, and Y. Massoud, “Many-to-many Recruitment and Scheduling in Spatial Mobile Crowdsourcing,” IEEE Access, March 2020.
12. A. Hamrouni, H. Ghazzai, M. Fikra, and Y. Massoud, “A Spatial Mobile Crowdsourcing Framework for Event Reporting,” IEEE Transactions on Computational Social Systems, January 2020.
13. A. Hamrouni, H. Ghazzai, T. Aleyani, and Y. Massoud, “An Evolutionary Algorithm for Collaborative Mobile Crowdsourcing Recruitment in Socially Connected IoT Systems”, Proceedings of the IEEE Global Conference on Artificial Intelligence and Internet of Things, December 2020.
14. A. Hamrouni, H. Ghazzai, T. Alelyani, and Y. Massoud, “Optimal Team Recruitment Strategies for Collaborative Socially Connected IoT Systems,” IEEE Technology Engineering Management Society International Conference, June 2020.
15. A. Khanfor, A. Hamrouni, H. Ghazzai, Y. Yang, and Y. Massoud, “A Trustworthy Recruitment Process for Spatial Mobile Crowdsourcing in Large-scale Social IoT,” IEEE Technology Engineering Management Society International Conference, June 2020.
16. A. Hamrouni, H. Ghazzai, T. Alelyani, and Y. Massoud, “A Stochastic Team Formation Approach for Collaborative Mobile Crowdsourcing,” Proceedings of the IEEE International Conference on Microelectronics, December 2019.
17. A. Hamrouni, H. Ghazzai, M. Frikha, and Y. Massoud, “A Photo-Based Mobile Crowdsourcing Framework for Event Reporting,” Proceedings of the IEEE International Midwest Symposium on Circuits and Systems, August 2019.