- FR
- EN
sana.mrabet@dauphine.psl.eu
Phone
: 01 44 05 45 70
Office
: LAMSADE
Sana Ben Hamida is an associate professor at Paris Nanterre University and an associate researcher at the computer science laboratory (LAMSADE) of Paris Dauphine University. Her main research topics are evolutionary algorithms, machine learning and related applications. Much of her work focuses on problems related to scaling evolutionary learning techniques for massive data. Sana Ben Hamida is also interested in the application of evolutionary algorithms to solve supervised and unsupervised learning problems in the fields of biology and biodiversity.
Ben Hamida S., Hmida H., Borgi A., Rukoz M. (2021), Adaptive sampling for active learning with genetic programming, Cognitive Systems Research, vol. 65, p. 23-39 
Ben M'Barek M., Borgi A., Bedhiafi W., Ben Hamida S. (2018), Genetic Algorithm for Community Detection in Biological Networks, Procedia Computer Science, vol. 126, p. 195-204
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2018), Scale Genetic Programming for large Data Sets: Case of Higgs Bosons Classification, Procedia Computer Science, vol. 126, p. 302-311
Abdelmalek W., Ben Hamida S., Abid F. (2009), Selecting the best forecasting-implied volatility model using genetic programming, Journal of Applied Mathematics, vol. 2009
Ben Hamida S., Cont R. (2005), Recovering volatility from option prices by evolutionary optimization, Journal of Computational Finance, vol. 8, n°4, p. 43-76
Ben Hamida S., Petrowski A. (2017), Evolutionary Algorithms John Wiley & Sons, Ltd, 236 p.
Ben Hamida S., Hmida H. (2023), Algorithm vs Processing Manipulation to Scale Genetic Programming to Big Data Mining, in Mansour Eddaly ; Bassem Jarboui ; Patrick Siarry, Metaheuristics for Machine Learning Springer International Publishing, p. 179-199
Ben Hamida S. (2016), Extension of Evolutionary Algorithms to Constrained Optimization, in Patrick Siarry, Metaheuristics, Amsterdam: Springer, p. 329-356
Braikia H., Ben Hamida S., Rukoz M. (2024), Random Forest Classifier for Marine Biodiversity Analysis, in , 2024 International Conference on Intelligent Systems and Computer Vision (ISCV), IEEE - Institute of Electrical and Electronics Engineers, 1-8 p.
Sena R., Ben Hamida S. (2024), ACTIVE SMOTE for Imbalanced Medical Data Classification, in Inès Saad ; Camille Rosenthal-Sabroux ; Faiez Gargouri ; Salem Chakhar ; Nigel Williams ; Ella Haig, Advances in Information Systems, Artificial Intelligence and Knowledge Management, Berlin Heidelberg, Springer International Publishing, 81-97 p.
Ben M'barek M., Ben Hamida S., Borgi A., Rukoz M. (2024), Evolutionary Graph-Clustering vs Evolutionary Cluster-Detection Approaches for Community Identification in PPI Networks, in Inès Saad ; Camille Rosenthal-Sabroux ; Faiez Gargouri ; Salem Chakhar ; Nigel Williams ; Ella Haig, Advances in Information Systems, Artificial Intelligence and Knowledge Management, Springer Nature Switzerland, 98-113 p.
Ben Hamida S., Benjelloun G. (2021), Extending DEAP with Active Sampling for Evolutionary Supervised Learning, in , SciTePress, 574-582 p.
Ben M'barek M., Ben Hamida S., Borgi A., Rukoz M. (2021), GA-PPI-Net Approach vs Analytical Approaches for Community Detection in PPI Networks, in , Amsterdam, Elsevier, 903-912 p.
Ben Hamida S., Benjelloun G., Hmida H. (2021), Trends of Evolutionary Machine Learning to Address Big Data Mining, in Inès Saad ; Camille Rosenthal-Sabroux ; Faiez Gargouri ; Pierre-Emmanuel Arduin, Information and Knowledge Systems. Digital Technologies, Artificial Intelligence and Decision Making, Springer International Publishing, 85-99 p.
Bousselmin K., Ben Hamida S., Rukoz M. (2020), Bi-objective CSO for Big Data ScientificWorkflows scheduling in the Cloud: case of LIGO workflow, in , 15th International Conference on Software Technologies (ICSOFT 2020), SciTePress, 615-624 p.
Ben Hamida S., Gorsane R., Mestiri K. (2020), Towards a Better Understanding of Genetic operators for Ordering Optimization -Application to the Capacitated Vehicle Routing Problem, in Marten van Sinderen, Hans-Georg Fill, Leszek Maciaszek, ?, SciTe Press, 461-469 p.
Ben M'barek M., Borgi A., Ben Hamida S., Rukoz M. (2019), Genetic Algorithm to Detect Different Sizes’ Communities from Protein-Protein Interaction Networks, in M. van Sinderen, L. Maciaszek, Proceedings of the 14th International Conference on Software Technologie, SciTe Press, 359-370 p.
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2019), Genetic Programming over Spark for Higgs Boson Classification, in W. Abramowicz, R. Corchuelo, Business Information Systems, 22nd International Conference, BIS 2019, Paris, Springer, 300-312 p.
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2019), A new adaptive sampling approach for Genetic Programming, in Plamen Angelov, Jaouad Boumhidi, Hani Hagras, 2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS), Marrakech, IEEE - Institute of Electrical and Electronics Engineers, 1-8 p.
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2017), Sampling Methods in Genetic Programming Learners from Large Datasets: A Comparative Study, in Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco, Advances in Big Data : Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece, Springer International Publishing, 50-60 p.
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2016), Hierarchical Data Topology Based Selection for Large Scale Learning, in Didier El Baz, Julien Bourgeois, 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), IEEE - Institute of Electrical and Electronics Engineers, 1221-1226 p.
Hmida H., Ben Hamida S., Borgi A., Rukoz M. (2016), Sampling Methods in Genetic Programming Learners from Large Datasets: A Comparative Study, in Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco, Advances in Big Data Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece, Springer, 50-60 p.
Ben Hamida Mrabet S., Rukoz M. (2016), Tuning Active Sampling Techniques for Evolutionary Learner from Big Data Sets: Review and Discussion, in Didier El Baz, Julien Bourgeois, Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), 2016 Intl IEEE Conferences, IEEE - Institute of Electrical and Electronics Engineers, 1206-1213 p.
Cazenave T., Ben Hamida S. (2015), Forecasting Financial Volatility Using Nested Monte Carlo Expression Discovery, in IEEE, 2015 IEEE Symposium Series on Computational Intelligence, Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers, 726-733 p.
Ben Hamida S., Schoenauer S. (2002), ASCHEA: new results using adaptive segregational constraint handling, in , Proceedings of the 2002 Congress on Evolutionary Computation, IEEE - Institute of Electrical and Electronics Engineers, 884-889 p.
Ben Hamida S., Schoenauer M. (2000), An adaptive algorithm for constrained optimization problems, in Marc Schoenauer, Kalyanmoy Deb, Günther Rudolph [et al.], International Conference on Parallel Problem Solving from Nature, Berlin Heidelberg, Springer, 529-538 p.
