Research directions
Formal ontology
Formal Ontology: Deep knowledge in the use and design of formal ontologies within the information technology realm. Experienced in crafting structured models to represent domain-specific knowledge, thus aiding in data integration, interpretation, and process automation. Proven expertise in utilizing representation languages to ensure interoperability across diverse systems and applications.
Digital Humanities
Deep expertise at the crossroads of technology and the humanities, leveraging digital tools to analyze, visualize, and interpret cultural and historical data. Proven competence in driving interdisciplinary projects, blending computer science with arts and social sciences. Committed to fostering a richer understanding of human phenomena through technological innovation.
Computational semantics
Proficient in understanding and applying computational methods to interpret and analyze the meaning of natural language. Skilled in leveraging algorithms and models to extract semantic information, ensuring accurate knowledge representation. Demonstrated experience in integrating semantic technologies into various applications to enhance data interpretation and user interaction.
Natural Language Processing
Natural Language Processing (NLP): Strong expertise in analyzing and modeling natural language using computational algorithms and techniques. Proficient in designing and developing applications focused on language understanding, text generation, and semantic analysis. Demonstrated experience in leveraging NLP to enhance human-computer interactions and extract meaningful insights from large textual datasets.
Information Retrieval
Proficient in deploying and optimizing automated systems for document searching and retrieval. Skilled in implementing algorithms to index, categorize, and retrieve documents based on relevance and context. Demonstrated experience in enhancing information accessibility and streamlining data management processes in large databases.
