Tsai-Ning Wang

Department of Industrial Design

Eindhoven University of Technology (TU/e)

Eindhoven, The Netherlands

I am a PhD student at Eindhoven University of Technology. My research focuses on the intersection of Artificial Intelligence and audio, with an emphasis on applications in healthcare. I am particularly interested in how multimodal systems can enhance the way we interact with and interpret medical information.

I hold a master’s degree in Language Technology from Uppsala University, where I developed a strong foundation in natural language processing and machine learning. My current work builds on that background by exploring intelligent systems that combine language and sound to support innovation in health. ✨🤖🩺

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selected publications

CaReAQA: A Cardiac and Respiratory Audio Question Answering Model for Open-Ended Diagnostic Reasoning

Tsai-Ning Wang, Lin-Lin Chen, Neil Zeghidour, and 1 more author

2025

Accepted at AHLI CHIL 2025

DOI Bib

@misc{wang2025careaqa,
  title = {CaReAQA: A Cardiac and Respiratory Audio Question Answering Model for Open-Ended Diagnostic Reasoning},
  author = {Wang, Tsai-Ning and Chen, Lin-Lin and Zeghidour, Neil and Saeed, Aaqib},
  year = {2025},
  eprint = {2505.01199},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
  doi = {10.48550/arXiv.2505.01199},
  url = {https://arxiv.org/abs/2505.01199},
  note = {Accepted at AHLI CHIL 2025},
}

Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding

Tsai-Ning Wang, Lin-Lin Chen, Neil Zeghidour, and 1 more author

2025

DOI Bib

@misc{wang2025semanticteachers,
  title = {Language Models as Semantic Teachers: Post-Training Alignment for Medical Audio Understanding},
  author = {Wang, Tsai-Ning and Chen, Lin-Lin and Zeghidour, Neil and Saeed, Aaqib},
  year = {2025},
  eprint = {2512.04847},
  archiveprefix = {arXiv},
  primaryclass = {cs.SD},
  doi = {10.48550/arXiv.2512.04847},
  url = {https://arxiv.org/abs/2512.04847},
}