Office C428
Email: jules.kreuerspam prevention@uni-tuebingen.de 
 

Research Interests

• Privacy-Preserving Machine Learning: Developing techniques to protect sensitive data while enabling effective machine learning models.
• Synthetic Genomic Data Generation: Creating realistic, artificial genomic datasets to support research and data privacy.
• Genomic Foundation Models: Building comprehensive models that capture the fundamental aspects of genomic data for advanced analysis and applications.
   

Academic Degrees

• M.Sc. in Bioinformatics, University of Tübingen, Germany, 2024.
  Thesis: Simulating and estimating the effect of genetransfer on bacterial pangenomes (GitHub)