Eduardo Calò

Eduardo Calò is a PhD Candidate in Natural Language Processing (NLP) at the Department of Information and Computing Sciences, Utrecht University, under Prof. Kees van Deemter. He works on the Interactive Natural Language Technology for Explainable Artificial Intelligence (NL4XAI) project, funded by EU Horizon 2020 under a Marie Sklodowska-Curie grant.

• Research Focus: Logic-to-text generation, formula simplification, and explainable AI
• Projects: LoLa system development, GECko+ error correction tool
• Expertise: Computational linguistics, hybrid symbolic-neural approaches, multilingual NLP

His work spans four key areas: (1) translating logical formulae into natural language with hybrid methods, (2) evaluating text quality through faithfulness and fluency metrics, (3) simplifying first-order logic expressions, and (4) developing writing assistance tools. He seeks to bridge symbolic logic with neural language models while addressing cross-linguistic challenges.

Recent publications demonstrate technical depth in formula minimization using QBF solvers, UX optimization for NLP interfaces, and discourse-level error correction systems. Collaborations include Albert Gatt, Jordi Levy, and Kees van Deemter across multiple EU-funded initiatives.