Publications & Research Output
Rewriting Tradition: Quantifying Change in Lady Gregory's Irish Legends
Explores textual transformations in Lady Gregory's Irish Legends using computational text analysis. Applies quantitative methods to examine stylistic and thematic changes over time, combining NLP, machine learning, and digital humanities methodologies for historical literary analysis.
Sentiment Reason Mining Framework for Analyzing Twitter Discourse on Critical Issues in US Healthcare Industry
A machine learning framework for analyzing Twitter discourse on critical US healthcare issues, applying sentiment analysis, NLP, clustering, and topic modeling to extract insights from public health discussions.
Text Reuse Detection with Large Language Models
Developing advanced text reuse detection methods using large language models, with a focus on unstable historical spellings, context sensitivity, and parallel text alignment. Part of the CASCADE MSCA project.
Interactive Visualization for NLP Interpretability
Building an open-source interactive visualization tool to surface model reasoning in text reuse and semantic change tasks — targeting usability by digital humanities and NLP researchers.
Parsing Hiberno-English Dictionary Entries: A Hybrid Rule-Based and LLM Approach
A hybrid system combining rule-based parsers and large language models to extract structured entries from Hiberno-English dictionary sources into a 14-field schema. Introduces a proxy evaluation framework, stratum-level agreement analysis, and audit methodology revealing two systematic root causes of LLM failure modes. Paper (17 pp.) under preparation; talk accepted at DHC 2026.
Trust & Agency in Agentic Cyber-Physical Systems
Investigating the gap between human intentionality, AI interpretation, and real-world actions in agentic systems. Contributes to the inTrusted framework for building trustworthy digital ecosystems through Living Lab approaches.