Vivien Goepp
Computational Biologist
Aachen, North Rhine-Westphalia, Germany
Summary
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Senior🎓
Top SchoolVivien Goepp is a computational biologist and postdoctoral researcher with eight years of experience applying statistical machine learning to single-cell and spatial transcriptomics, currently at KramannLab, Uniklinik RWTH Aachen, focusing on the cellular drivers of kidney fibrosis. With a PhD in Mathematics and Statistics and engineering and master’s training in computational mathematics from CentraleSupélec and Sorbonne/Paris Diderot, she blends rigorous theory with practical tool-building in Python and R. Previously at MINES ParisTech she developed a causal biomarker selection method, parallelized an R package for network-based genomic analysis, and taught intensive courses on variable selection. Comfortable across bioinformatics, network analysis, and scalable implementations (Docker, plink, Jupyter), she bridges statistical innovation and reproducible software for genomics studies.
8 years of coding experience
2 years of employment as a software developer
Engineer's degree, Computational and Applied Mathematics, Engineer's degree, Computational and Applied Mathematics at CentraleSupélecDoctor of Philosophy - PhD, MATHEMATICS AND STATISTICS, Doctor of Philosophy - PhD, MATHEMATICS AND STATISTICS at Univ Paris DiderotMaster's degree, Computational and Applied Mathematics, Highest honours, Master's degree, Computational and Applied Mathematics, Highest honours at Sorbonne University
Github Skills (35)
seurat9
genomics8
bioinformatics7
cran7
shiny-apps7
single-cell-analysis6
single-cell-genomics6
machine-learning5
notebook4
r-package4
python4
gwas4
jupyter-notebook4
immunology3
pipeline3
Programming languages (3)
Github contributions (5)
goepp/ml-in-genomics-2021
Mar 2021 - May 2021
Contributions:41 commits, 29 pushes, 1 branch in 1 month
goepp/graphseg
May 2019 - Jun 2022
Contributions:1 release, 66 commits, 29 pushes in 3 years 1 month
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