Britta Velten
Machine Learning Engineer at University Heidelberg
Heidelberg, Baden-Württemberg, Germany
Summary
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SeniorBritta Velten is a tenure-track professor and machine learning engineer specializing in multifactorial data analysis for the life sciences, with nine years of experience bridging mathematics, statistics, and computational biology. Trained as a mathematician with a PhD in Statistics from ETH Zurich/EMBL and postdoctoral work at DKFZ and the Wellcome Sanger Institute, she develops statistical and ML methods that translate complex omics data into biological insight. Based at Heidelberg University’s Centre for Organismal Studies and Centre for Scientific Computing, she leads a research group focused on method development and interdisciplinary collaboration. Her background blends rigorous theoretical training with hands-on application to high-throughput biological data, and her work is accessible via the Velten Group website.
9 years of coding experience
Github Skills (21)
decomposition10
factor-analysis10
dtw10
topological-data-analysis10
meta-analysis10
factor10
python8
r-package8
bioconductor7
genomics7
bioinformatics6
cffi5
r5
interoperability5
data-analysis4
Programming languages (4)
Github contributions (5)
bioFAM/mofapy2
Oct 2019 - Jul 2021
Contributions:155 commits, 3 PRs, 8 pushes in 1 year 9 months
factor-analysisfactormulti-omicsomics
bioFAM/MEFISTO_analyses
Oct 2020 - Jul 2021
Repository containing the code to reproduce the analyses contained in the MEFISTO manuscript
Contributions:9 commits, 1 PR, 7 pushes in 9 months
reproducemanuscriptanalyses
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