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 generative modeling, causal inference, and computational biology, with a focus on precision medicine applications and developing models that simulate single-cell response to perturbations. Feel free to reach out to me if you have similar research interests and would like to collaborate on a project!
Interests
- Machine Learning
- Generative Models
- Causal Inference
- Precision Medicine
- Virtual Cells
Background
You can find my full CV here.
- 2024 - | PhD, Machine Learning, BIFOLD & Machine Learning Group, TU Berlin, Germany
- 2024 - | Data Scientist, Aignostics, Berlin, Germany
- 2023 - 2024 | Data Scientist Intern, Aignostics, Berlin, Germany
- 2021 - 2024 | MSc in Computer Science, TU Berlin, Germany
- 2018 - 2021 | BSc in Computer Science, Leibniz University Hannover, Germany
Publications
See my Google Scholar profile for a list of my publications.
Teaching
See the Machine Learning Group’s teaching page for courses I am involved in:
- Winter 2025/26: Project Machine Learning
- Summer 2025: Python for Machine Learning
News
2024
- November: Our findings paper xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer was accepted at the Machine Learning for Health (ML4H) symposium in Vancouver!
- October: I started my PhD at BIFOLD and the Machine Learning Group at TU Berlin while continuing to work with Aignostics on machine learning for precision medicine!
- April: After defending my master’s thesis, I joined Aignostics full-time, focusing on data-driven drug target identification in collaboration with Bayer Pharmaceuticals.
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.