Merhaba! Hi! Hallo! Bonjour!

I’m a PhD candidate in the Integrative Cellular Biology and Bioinformatics Laboratory at Saarland University, working where machine learning meets gene regulation.

I develop interpretable, biologically informed models that help explain how cells with identical DNA establish and change their identity. A central theme of my work is building graph neural networks that embed real biological structure, such as transcription-factor interaction networks, directly into how they learn, so that predictions arrive with explanations a biologist can actually use. My research spans single-cell and bulk multi-omics, explainable AI, and causal inference, and has contributed to studies of the human immune epigenome (Nature Genetics, 2025).

I also care deeply about open-source software, and I develop and maintain genomics packages in R and Python, including deconvR (Bioconductor), methylTFR, and ChrAccR.

My research interests include:

• Explainable and interpretable machine learning
• Graph neural networks for gene regulation
• Single-cell and bulk multi-omics integration
• Causal inference in epigenomics
• Open-source software development for bioinformatics

I’m also an active member of the Bioinformatics Research Network, where I volunteer as a skill-assessment reviewer, evaluating the code efficiency and cleanliness of BRN trainees.