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👀: NLP, LLMs, Recommender Systems, Personalization, Information Retrieval, Machine/Deep Learning 🎓: PhD Candidate @Sorbonne University | MVA, ENS-PS
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Review_based_Recommender_Systems_Baselines
March 16, 2026 – Present
Review_based_Recommender_Systems_Baselines — GitHub repository
View ProjectMemory_Statement_Explainable_Recommendation
March 14, 2026 – Present
Memory_Statement_Explainable_Recommendation — GitHub repository
View Projectfactual_explainable_recommendation
October 22, 2025 – Present
Factual Explainable Recommendation Framework: Datasets & Evaluation
View Projectaspect_explainable_recommender
December 7, 2024 – October 6, 2025
Unified Attention-Based Framework for Aspect Ratings Prediction and Personalized Review Generation
View Projectllms_recommender
May 20, 2024 – September 20, 2024
[Recommender Systems and Natural Language Processing]
View Projectm1-rital
February 9, 2023 – May 23, 2023
Solutions aux TPs de l'UE RITAL (Recherche d'Information et Traitement Automatique du Language) que j'ai suivi lors de mon second semestre au master DAC à Sorbonne Université.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong initiative through numerous personal projects, particularly in the domain of explainable AI and recommender systems. This indicates a proactive and research-oriented mindset. The diversity of projects within a specific domain (NLP/Recommenders) suggests a deep interest and potential for focused contribution. However, without information on team experience or broader interests, a comprehensive cultural fit assessment is limited.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style.