Dr. Jaber  Jemai
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Dr. Jaber Jemai

Associate Professor and Dean
Ama International University Bahrain, Bahrain


Highest Degree
Ph.D. in Computer Information Systems from University of Tunis, Tunisia

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Biography

Dr. Jaber Jemai holds a position of Associate Professor and Dean at College of Computer Studies, AMA International University Bahrain, Salmabad, Kingdom of Bahrain. He has completed his Ph.D. in Computer Information Systems from High Institute of Management, University of Tunis. Previously he was appointed as Teaching Assistant at University of Tunis, Assistant Professor at University of Tunis El Manar, and Assistant Professor at Imam Mohammed Ibn Saud Islamic University in Riyadh, Saudi Arabia. His main area of research interest focuses on Computational Intelligence, Machine learning, Big Data, Approximate Optimization techniques: (Meta, Hyper) - Heuristics, Cloud Computing. Dr. Jaber has published 7 research article in international journal and 12 national international conference proceeding. He has completed 2 funded research projects. Dr. Jaber is member of the accreditation committee of the information system Department in the college of computer and information sciences, Laboratory of Operations Research, Decision and Process Control-LARODEC, High Institute of Management of Tunis, and member of Tunisian Management Science Society. He is also serving as referee for Neural Networks, International Journal of Operations and Quantitative Management, International Journal of Neural Systems, OR Spectrum, and International Joint Conference on Neural Networks IJCNN and European Conferences on Symbolic and Quantitative Approaches to Reasoning with Uncertainty ECSQUARU.

Area of Interest:

Computer Sciences
100%
Computational Intelligence
62%
Machine Learning
90%
Heuristic
75%
Cloud Computing
55%

Research Publications in Numbers

Books
0
Chapters
0
Articles
0
Abstracts
0

Selected Publications

  1. Chaieb, M., J. Jemai and K. Mellouli, 2015. On the Relationships Between Sub Problems in the Hierarchical Optimization Framework. In: Current Approaches in Applied Artificial Intelligence, Ali, M., Y.S. Kwon, C.H. Lee, J. Kim and Y. Kim (Eds.). Springer, New York, USA., ISBN: 9783319190662, pp 232-241.
  2. Chaieb, M., J. Jemai and K. Mellouli, 2015. Decomposability Conditions of Combinatorial Optimization Problems. In: Current Approaches in Applied Artificial Intelligence, Ali, M., Y.S. Kwon, C.H. Lee, J. Kim and Y. Kim (Eds.). Springer, New York, USA., ISBN: 9783319190662, pp: 242-251.
  3. Chaieb, M., J. Jemai and K. Mellouli, 2015. A hierarchical decomposition framework for modeling combinatorial optimization problems. Procedia Comput. Sci., 60: 478-487.
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  4. Jemai, J., 2014. A novel approach for solving the dynamic vehicle routing problem based on hierarchical self-organizing maps. Int. J. Comput. Intell. Applic., Vol. 13. 10.1142/S1469026814500254.
    CrossRef  |  Direct Link  |  
  5. Jemai, J., M. Zekri and K. Mellouli, 2012. An NSGA-II Algorithm for the Green Vehicle Routing Problem. In: Evolutionary Computation in Combinatorial Optimization, Hao, J.K. and M. Middendorf (Eds.). Springer, New York, USA., ISBN: 9783642291241, pp: 37-48.
  6. Jemai, J. and K. Mellouli, 2008. A neural-tabu search heuristic for the real time vehicle routing problem. J. Math. Mod. Algorithms, 7: 161-176.
    CrossRef  |  Direct Link  |