Amel Mhamdi
Data scientist
39 years old
Driving License
Professional Status
Employed
Available
About Me
Experte intelligence artificielle diplômée d'un Doctorat en Intelligence Artificielle en 2016, je me suis spécialisée sur l'analyse des données ainsi que l'automatisation des processus de travail et la prédiction via les Framework de l'IA et les algorithmes de Machine Learning.
Éternelle optimiste et curieuse de nature, je m'intéresse à tout ce qui me passe sous la main.
J'aime apprendre de nouveaux métiers et outils liés au Data, IA et le cloud et je suis toujours prête à aider mon équipe pour atteindre nos objectifs !
Éternelle optimiste et curieuse de nature, je m'intéresse à tout ce qui me passe sous la main.
J'aime apprendre de nouveaux métiers et outils liés au Data, IA et le cloud et je suis toujours prête à aider mon équipe pour atteindre nos objectifs !
Context:
Although the problem of graph editing (CE) has been defined since 1964, it is still very much studied. One of the reasons is that the graph editing problem occurs in many applications such as, for example, species analysis, a problem in the field of genetics. The difficulty is to choose a representation that guarantees an effective treatment of this problem. Several representations have emerged, such as the one that uses: the logic of the propositions (SAT) and its extensions (2-SAT, 3-SAT, MAX-SAT, ...), the formalism of the problem of satisfaction of the CSP constraints.
Contribution:
Our contribution in the field of the classification under constraints is varied according to two main axes:
Results:
the goal is to propose a new approach to deal with graph editing. This approach is based on the formalism of the problems of satisfaction of valued constraints.
This formalism provides a rigorous framework, more general than that of the CSP and especially powerful algorithms to efficiently solve combinatorial problems.
Publications:
Technical environment:
ToolBar2, C ++, Python
Although the problem of graph editing (CE) has been defined since 1964, it is still very much studied. One of the reasons is that the graph editing problem occurs in many applications such as, for example, species analysis, a problem in the field of genetics. The difficulty is to choose a representation that guarantees an effective treatment of this problem. Several representations have emerged, such as the one that uses: the logic of the propositions (SAT) and its extensions (2-SAT, 3-SAT, MAX-SAT, ...), the formalism of the problem of satisfaction of the CSP constraints.
Contribution:
Our contribution in the field of the classification under constraints is varied according to two main axes:
- Methodological: we propose methodological approaches adapted to the problems of graph editing and the problem of classification by deletion of edges.
- Technique: we introduce new techniques (heuristic search algorithms, global constraints) to fill some gaps identified thanks to our methodology.
Software: The implementation of these techniques in a constraint solver facilitates their diffusion and their implementation in various applications.
Results:
the goal is to propose a new approach to deal with graph editing. This approach is based on the formalism of the problems of satisfaction of valued constraints.
This formalism provides a rigorous framework, more general than that of the CSP and especially powerful algorithms to efficiently solve combinatorial problems.
Publications:
- "Constraint programming approach to the Zahn's decision problem". In the Proceeding of the International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2014), Salamanca, Spain, June 2014.
- "A constraint programming approach to the cluster deletion problem". Proceeding of the 13th Scandinavian Conference on
Artificial Intelligence Halmstad, Sweden, November 5-6, 2015
- "Classification of genes based on weighted PUC".
The Eleventh French Journées de Programmation by Constraints, (JFPC 2016).
- "LDS vs FPT method for cluster deletion International conference of artificial intelligence tools.
28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016, San Jose, CA, USA, November 6-8, 2016.
- "A constraint programming approach to the cluster editing problem". International Journal of Imaging and Robotics (ISSN 2231-525X), August 2015.
Technical environment:
ToolBar2, C ++, Python
