Biography
I am a Maître de Conférences (Associate Professor) at Paris-Saclay University since September 2024. Previously, I worked at Télécom Paris, Institut Polytechnique de Paris. During my PhD at Conservatoire National des Arts et Métiers and Sorbonne University, I focused on entity linking and data quality of knowledge graphs.
My research interests include artificial intelligence, knowledge graphs, and natural language processing.
- Artificial Intelligence
- Knowlegde Graphs
- Information Extraction
- Knowledge Representation
- NLP
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PhD in Artificial Intelligence, 2020
Sorbonne University and CNAM
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M.Sc. in Artificial Intelligence, 2016
CNAM
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M.Sc. in Mathematics, 2008
CY Cergy Paris University (incomplete)
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Research Interests
Experience
Works on LLM, logic, and knowledge graphs.
Responsibilities include:
- Collaborations with industrial and academic partners
- Managing meetings with partners
- PhD and student supervision
Responsibilities include:
- Requirements analysis, solution design, development, testing and validation, maintenance, documentation to meet the company’s needs for various projects: e-commerce sites, inventory management, embedded systems, etc.
- Student supervision
- Team management
Supervision involvement
- Simon Coumes: PhD student at Telecom Paris (2022-)
- Chadi Helwe: PhD student at Telecom Paris (2022-2024)
- François Amat: PhD student at Telecom Paris (2022-)
- Syrine El Aoud: master student research project at Telecom Paris (2021)
- Khalil Halloul: BSc student (2013-2014)
- Ayoub Mountassir: MSc student (2013-2015)
- Master student groups at Telecom Paris for student projects
Projects
This enhanced version of the YAGO knowledge base integrates extensive elements of the Wikidata taxonomy, providing a cleaner, logically consistent structure for improved information retrieval and automated reasoning.
Posts
This vision and survey paper is part of the NoRDF project and is a joint work between Pierre-Henri Paris, Syrine El Aoud and Fabian Suchanek (Télécom Paris, DIG team).
For more details, you can check the full AKBC paper here.
This is a joint work between Pierre-Henri Paris and Fabian Suchanek (both at Télécom Paris, DIG team).
Non-Named Entities?
Human texts usually contain a lot of noun phrases that often function as verb subjects and objects, as predicative expressions and as the complements of prepositions. When building knowledge bases, proper nouns in noun phrases are extracted and used as entities equipped with facts to populate knowledge bases. During this process, noun phrases that are not proper nouns are left unmapped, thus ignoring a vast amount of information. Consider the following example which contains a named entity and two non-named entities: