
Nasreddine Cheniki
Data Scientist | Semantic Web & Large Language Models
Salaire / Taux journalier
Tours, France
Freelance
Expertises
Langues
À propos
Introduction
Ph.D. in Computer Science with 7+ years specializing in AI, semantic web, and large language models. Successfully designed and deployed a metadata recommendation system for the European Commission using advanced NLP and semantic analysis, resulting in expanded project funding. Expert in RAG, transformers, ontology-based data integration, and semantic modeling—delivering AI-driven solutions that transform complex data into actionable insights.
Expérience de travail
Data Scientist and Semantic Web Consultant
infeurope S.A.
janv. 2022 - Présent
4 ans 10 mois
Luxembourg
Designed and implemented a document metadata recommendation system for CELLAR, the European Commission’s publication management system. Key responsibilities: * Prepared the technical specifications for the project * Installed and maintained SeTA (Semantic Text Analysis Tool), a powerful large language model tool for text analysis, utilized for assessing document similarity. * Designed and executed analytical experiments to evaluate SeTA’s potential for metadata recommendation using its text analysis capabilities. * Developed and implemented a metadata recommendation system * Created a classification and clustering approach for documents Key achievements: * Implemented a metadata recommendation system for cataloging, which received overwhelmingly positive feedback, leading to increased budget allocation for the project. * Published a scientific paper in an international conference
Research And Teaching Assistant (ATER)
Université François Rabelais de Tours
sept. 2017 - juil. 2021
3 ans 11 mois
Tours Area, France
Research and projects: ================= I contributed to the SmartLoire project that aims to provide visitors of "Vale-de-Loire" region with personalized itineraries according to their preferences. The first objective is to integrate tourism data from multiple sources using ontologies. The second objective is to analyze visitors' itineraries to identify their behaviors and to extract knowledge from the trajectory mining. Key responsibilities: ------------------------------ * Design a graph model (using ontologies) to merge heterogeneous tourism data. * Define scalable data integration architecture. * Mapping the integrated data with the Linked Open Data graph. * Design and implement semantic search/recommendation algorithms for tourism trip planning based on the resulted graph database. * Train, supervise, and monitor bachelor and Ph.D. students contributing to the project. Key achievements: ---------------------------- * Publishing many research papers related to the project. All papers were published and presented in English. * Developing an open-source Java Library called LDS that provides calculation of LOD-based semantic similarity. It is used in the project to propose recommendations for tourism services and itinerary recommendations. Teaching Assistant: =============== All my teachings have been done at the University of Tours. I was involved in many courses, among others: * Databases & Web programming * Algorithms and object programming - Java/Python * (Advanced) Databases * Developing Mobile application using Android * Operation systems
Visiting Researcher
Université François Rabelais de Tours
oct. 2016 - mai 2017
8 mois
Tours Area, France
Web developer
IT-Solutions (Optymitis)
août 2011 - juil. 2012
1 an
Web developer
Formation
Université 20 août 1955 - Skikda
Master, Computer Systems
Université des Sciences et de la Technologie 'Houari Boumediène'
Doctor of Philosophy (Ph.D.), Computer Science
During my thesis, I worked on the semantic discovery of mobile (contextual) services. I used ontologies and LOD information to annotate service descriptions and propose semantic similarity and discovery algorithms. Key responsibilities: ------------------------------ * Design and propose a new Ontology extension that supports mobile services semantic description. * Propose a discovery framework that allows semantic matching of functional and non-functional (contextual) service descriptions. * Propose annotation mechanism to enrich Service descriptions with ontology concepts and semantic resources provided by the LOD. * Design and development of Semantic Similarity algorithms and measures based on LOD data to improve service matching. Key achievements: ---------------------------- * Publishing many research papers related to the thesis. * Propose efficient semantic services matchmaking algorithms that are reused and extended in SmartLoire project.
Licences et certifications
Fundamentals of Deep Learning
Délivré le : août 2022
Programming Mobile Applications for Android Handheld Systems
Délivré le : mars 2014