Katarína Grešová is a postdoctoral machine learning researcher with nine years of experience applying deep learning to genomics and structural biology, currently working on protein structure analysis and genomic sequence classification at the Max Delbrück Center in Berlin. She builds end-to-end ML solutions—from scalable HPC pipelines and production deployments to model interpretation—bridging computational rigor with biological insight. Her work includes developing Genomic Benchmarks and miRBench, publishing novel interpretation methods (e.g., Attribution Sequence Alignment), and leading workshops that train researchers in deep learning and XAI for biology. With international stints at NIH, University of Malta, and industry roles integrating vision and NLP systems, she blends academic depth (PhD in Genomics and Proteomics) with practical engineering chops across Python and C++ codebases. Colleagues value her technical leadership and mentorship, and she is open to collaborations that translate ML advances into real-world healthcare and biology applications.
9 years of coding experience
7 years of employment as a software developer
PhD Genomics and Proteomics, PhD Genomics and Proteomics at Masarykova univerzita
Master's degree Bioinformatics and biocomputing, Master's degree Bioinformatics and biocomputing at Brno University of Technology
Benchmarks for classification of genomic sequences
Contributions:1 release, 2 reviews, 122 commits in 9 months
pytorchdeep-learninggenomics-datadatasetgenomics
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Katarína Grešová - Postdoctoral Researcher at Max Delbrück Center