Betty van Aken, M.Sc. Profile

Betty started working at the DATEXIS team as a Research Assistant in 2018.

She graduated with a Master's degree in Media Informatics from the Beuth University of Applied Sciences in Berlin in 2017. During and after her studies she used to work as a Software Engineer. One of her focuses and the research topic of her master's thesis was the development of chatbot applications.

At DATEXIS Betty is currently working on the project NOHATE, funded by the Federal Ministry of Education and Research. The project aims to find solutions for the detection of Hatespeech in online discussions with the help of Deep Learning techniques.

In addition to that, Betty is doing research in NLP for the medical domain. Specifically she wants to find out how to use information written down in clinical notes to improve decision support systems for medical professionals.

 

Research Interests

  • Deep Learning
  • NLP for the medical domain
  • Explainability
  • Chatbots

 

Demos

 

Publications

  • Betty van Aken, Benjamin Winter, Felix A. Gers and Alexander Löser. VisBERT: Hidden-State Visualizations for Transformers. Accepted to The Web Conference 2020 (WWW'20) Demo Track [Code]
  • Sebastian Arnold, Betty van Aken, Paul Grundmann, Felix A. Gers and Alexander Löser. Learning Contextualized Document Representations for Healthcare Answer Retrieval. Accepted to The Web Conference 2020 (WWW'20) [PDF] [Code].
  • Betty van Aken, Benjamin Winter, Felix A. Gers and Alexander Löser. How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations. The 28th ACM International Conference on Information and Knowledge Management (CIKM'19) [PDF] [Code]
  • Betty van Aken, Julian Risch, Ralf Krestel, Alexander Löser. Challenges for Toxic Comment Classification: An In-Depth Error Analysis 2nd Workshop on Abusive Language Online EMNLP 2018 [arXiv]

 

Advised Bachelor- / Mastertheses

  • A. Allhorn, "Transfer Learning for Hate Speech Detection", Master Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2020
  • S. Herrmann, "Generating Electronic Health Records: an Investigation on Gender-Medicine and Rare Diseases", Bachelor Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2020.

 

Contact

E-Mail: bvanaken (at) beuth-hochschule.de

https://www.linkedin.com/in/betty-van-aken/