معرفی
Julien Romero serves as Maître de Conférences (Associate Professor) at Telecom SudParis, Institut Polytechnique de Paris, where he conducts research within the SAMOVAR laboratory. His work bridges artificial intelligence, database systems, and natural language processing with practical applications in knowledge representation and recommender systems.
Romero earned his PhD in Artificial Intelligence from Institut Polytechnique de Paris in 2020 with a thesis on harvesting commonsense knowledge from web services. His research focuses on extracting and refining commonsense knowledge from unconventional sources including children's texts, query logs, and web content. He develops techniques for knowledge graph construction, query rewriting, and heterogeneous graph-based recommendation systems.
Analysis of his 12 publications (2019-2024) reveals a strong trajectory from foundational database research toward applied AI systems. His work consistently addresses real-world challenges like job recommendation cold-start problems and commonsense knowledge base cleaning, demonstrating increasing technical sophistication through generative translation methods and heterogeneous graph approaches. Key publication venues include IEEE TKDE, CIKM, ISWC, and EMNLP.
Romero actively mentors students through SAMOVAR laboratory projects, with research opportunities spanning knowledge engineering, natural language processing, and educational tool development. His Pyformlang library exemplifies his commitment to making theoretical computer science accessible. Current projects like TIMBRE (2024) indicate active industry-relevant research in professional recruitment systems.
The SAMOVAR laboratory provides Romero's research environment, focusing on networks, computer science, and communication systems. His work within this framework emphasizes practical applications of theoretical concepts, particularly in knowledge representation and AI-driven recommendation systems. Ongoing projects suggest continued innovation in leveraging generative AI for knowledge base refinement and heterogeneous information network analysis.
