I am a PhD student in the Machine Learning Group at TU Berlin and at the Berlin Institute for the Foundations of Learning and Data (BIFOLD). In addition, I am a Data Scientist at Aignostics, where I am working on data-driven drug target identification in collaboration with Bayer Pharmaceuticals. During my Master’s in Computer Science at TU Berlin, I worked on explainable graph neural networks for survival prediction in lung cancer and was funded by the Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA).

My research lies at the intersection of machine learning and biomedicine, primarily focusing on developing robust and interpretable models for patient stratification and drug target identification using multi-omics biomedical data. Feel free to reach out to me if you have similar research interests and would like to collaborate on a project!

Interests

  • Machine Learning for Precision Medicine
  • Multi-omics Data
  • Generative Models
  • Multimodal Learning
  • Geometric Deep Learning

Background

See my LinkedIn profile for my full CV.

Publications

See my Google Scholar profile for a list of my publications.

News

2024

2023

  • October: I received a Konrad Zuse Master’s in AI Scholarship from the Zuse School ELIZA!
  • August: I finished my internship and started working on my master’s thesis on explainable graph neural networks for survival prediction in lung cancer.
  • February: I joined Aignostics as a Data Scientist Intern! Looking forward to putting my skills into practice and diving into AI-powered precision diagnostics.