Natural Language Processing For Expert Domains (ExpNLP)

At ExpNLP, we work on Natural Language Processing applied to expert domains, with a focus on the real-world impact of AI.

Our interests include:

  • Evaluation of Large Language Models in expert domains including software engineering, healthcare, and industry dynamics.
  • Reliable integration of multimodal data in AI to help domain experts in their work.
  • Expert-AI interaction and collaboration.

People

PhD Students

Doan

Doan Nam Long Vu

Topics: Multimodal AI for mental health

TODO - bio

Anna

Anna Mokhova

Topics: Expert-AI collaboration in coding

TODO - bio

Ruilong

Ruilong Wang

Topics: Multimodal RAG systems for automotive applications

TODO - bio

Student Thesis

Finished

  • Enhancing Natural Language Inference in Biomedical Applications Using Large Language Models (finished) — Kai Zhao

Ongoing

  • Time-Stamped Graphs for Cross-Year Reasoning in VolksWagen Annual Reports (ongoing) — Karim Abdelrahman
  • Contrast Set Generation for Evaluation QA Models in Annual Report reasoning (ongoing) — Cagin Senemoglu
  • Expressive Text-To-Speech Generation and Evaluation for Therapist-Client Dialogues (ongoing) — Marleen Sinsel
  • Synthetic Therapist-Client Conversation Generation From Questionnaires (ongoing) — Mohamed Aziz Boudabous

Openings / Collaboration

If you are interested in working with us, feel free to get in touch by email.

At the moment, we welcome application from B.Sc. and M.Sc. thesis students who want to work on compatible topics. If you are interested, feel free to contact Dr. Simone Balloccu. If possible include a grade transcript, an initial topic (or at least proposals), and a CV.