Paul Sheridan

Paul Sheridan is an Assistant Professor at the School of Mathematical and Computational Sciences, University of Prince Edward Island, specializing in text analysis and ontologies for computational literary studies. He develops novel term weighting schemes through statistical significance testing to improve document retrieval, classification, and summarization methods. His Literary Theme Ontology (LTO) provides the first controlled vocabulary of literary themes for media annotation and information retrieval.

• Research Grants: AI/machine learning for engine maintenance (2024), keyword extraction efficacy analysis (2023–2024), GPT-2 unnatural language generation (2022–2025)
• Academic Leadership: Statistics and Analytics Program Lead (2024–present), ACENET Research Directorate member

His recent publications focus on lexical diversity analysis, term dispersion quantification, and statistical foundations of TF-IDF. He supervises students in projects spanning energy-efficient NLP, causal inference in finance, and low-resource language embeddings. Paul actively contributes to open-source projects like stoRy and PAFit packages.