PhD Candidate in Cognitive Informatics at Université du Québec à Montréal (UQAM)

Research Interests:

• 🤖 Algorithmic Bureaucracy & Governance
• 🔍 Explainable AI (xAI) & Transparency
• 📊 Recommendation Systems & Collaborative Filtering
• 🌐 Digital Sociology & Information Credibility
• ⚖️ AI Ethics & Accountability

A hybrid fact-checking system combining predicate-logic rules, ontologies (OWL), and neuro-symbolic AI to evaluate the credibility of information sources.

SysCRED est un système hybride de fact-checking combinant :

• Symbolic AI : Raisonnement par règles et ontologies (OWL/RDF)

• Neural AI : Transformers pour NER, sentiment, cohérence

• IR Engine : Recherche d’évidence (BM25, TF-IDF, TREC)

• GraphRAG : Mémoire contextuelle par graphe de connaissances

• E-E-A-T : Scoring qualité Google (Experience, Expertise, Authority, Trust)

• Technologies: Python, NLP, OWL Ontologies, Machine Learning, Neuro-symbolic AI

• Status: Active Research (Doctoral Project)

• 📂 Repository

• 📄 Modeling Paper

• 📄 Ontology Paper

• 📄 Beamer Presentation - (PDF)

Le Léviathan Algorithmique : pouvoir, opacité et responsabilité à l'ère de l'intelligence artificielle

• Modeling a Hybrid System for Verifying Information Credibility (2025)

• Hybrid System Ontology for Information Source Verification (2025)
  

Evaluation of Information Retrieval Models on TREC AP 88-90 (2025)

Évaluation comparative de modèles de recherche d'information sur les collections TREC AP 88-90.

Technologies : Python • Information Retrieval • BM25 • TF-IDF • Vector Space Models

Résultats :

• 📊 Analyse de ~243,000 documents
• 📈 Comparaison BM25 vs. VSM
• 🎯 Métriques MAP, NDCG, Precision@K

📄 Lire l'article

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A hybrid system combining predicate logic and ML/AI for assessing information source credibility.

• Technologies: Python, NLP, Ontologies (OWL), Machine Learning
• Status: Active Research
• 📂 Repository | 📄 Paper

OWL ontology for modeling information verification systems.

• Technologies: OWL, RDF, Protégé
• Status: Published
• 📂 Repository | 📄 Paper

Neural machine translation system with attention mechanisms.

• Technologies: Python, TensorFlow, PyTorch, NMT
• Status: Completed
• 📂 Repository | 📄 Paper

Programming Languages:

AI/ML Frameworks:

Research & Productivity Tools:

• 🔬 Completing PhD dissertation on algorithmic bureaucracy
• 📝 Publishing research on AI transparency and accountability
• 💡 Developing explainable AI frameworks for recommendation systems
• 🌍 Contributing to open science and reproducible research

Année	Titre	Type	DOI
2025	Le Léviathan Algorithmique : pouvoir, opacité et responsabilité à l'ère de l'intelligence artificielle	Examen de synthèse doctoral
2025	Modeling a Hybrid System for Verifying the Credibility of Information Sources	Preprint
2025	Hybrid System for Verifying Credibility: An Ontology	Preprint
2025	Evaluation of Information Retrieval Models on TREC AP 88-90	Preprint
2025	Development and Evaluation of an English-to-Russian Neural MT System	Preprint

• 🌐 Website: dominiqueloyer.github.io
• 📧 Email: 2e2g3zhvt@mozmail.com
• 💼 LinkedIn: linkedin.com/in/dominique-loyer-456ab739b
• 🔬 ORCID: 0009-0003-9713-7109
• 📚 Google Scholar: Profile
• 🔍 ResearchGate: Dominique Loyer

Unless otherwise specified, research code is released under MIT License.
Academic publications follow their respective copyright agreements.

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