themes

Research themes of the group (with entry points to projects, datasets, demos, and student outcomes).

Research themes (entry points)

AI for Science
Systems that help researchers cope with information overload: literature discovery, evidence-backed QA, “papers to insights”.
Trustworthy LLMs and Evidence-Grounded Generation
Reliable LLM assistants: RAG, citation-aware/verifiable generation, evaluation methodology, and safety/bias analysis.
Knowledge Graphs and Graph Machine Learning
Structured knowledge integration for AI: large-scale KGs, graph retrieval/linking, graph ML, and neuro-symbolic methods.
Plain Language and Accessible Communication
Inclusive plain-language transformation and text simplification for real-world documents and websites.


If you are a student and want to work with us, start here: /student_thesis/ (and /how-we-work/).