I am building fast, memory-efficient software to study signaling on the single-cell level. Leveraging novel single-cell datasets like sequencing based single-cell protein measurement technologies I am working on scalable tools to decode cellular signaling networks. Therefore, i develop solutions from the raw data processing to methods to infer singlaing networks.
I develop fast, memory-efficient, and scalable software solutions for single-cell data analysis, with a strong focus on extracting meaningful biological insights from complex datasets. My current research centers on (phospho)protein data, where I study correlation patterns at the single-cell level to infer signaling networks. My work spans the full analytical pipeline, from raw data processing and normalization to downstream network analysis.
I am proficient in C++, R, and Python, and particularly interested in performance-oriented computing and scalable algorithm design for large biological datasets. I am currently a PhD student based in Leiden, completing my doctorate at the Netherlands Cancer Institute (NKI) in collaboration with VU Amsterdam. I previously studied Biotechnology at TU Berlin and Bioinformatics at the University of Hamburg.