Karel Břinda is a permanent researcher and PI at Inria Rennes with 11 years of experience at the intersection of algorithms and computational biology, focusing on genomics, pathogen surveillance, and rapid diagnostics. He leads a group developing resource-frugal, alignment-free DNA search and analysis methods aimed at enabling point-of-care inference of antibiotic resistance and real-time scanning of public sequence databases. Before joining Inria in 2022 he held research positions at Harvard Medical School and the Harvard T.H. Chan School of Public Health, where he helped create Genomic Neighbor Typing — a method that delivers resistance predictions in minutes and was published in Nature Microbiology. His PhD work produced several practical tools for NGS mapping and metagenomic classification, and earlier engineering work produced automated tactile maps for the blind, showing a knack for turning theory into impactful software. Based in Rennes, he combines deep theoretical understanding of sequence algorithms with pragmatic, end-to-end implementations that bridge lab workflows and epidemiological applications.
11 years of coding experience
14 years of employment as a software developer
High school diploma, General Studies, High school diploma, General Studies at Gymnázium–Jaroslava–Heyrovského grammar school in Prague
Master of Science - MSc (Ing), Mathematical Computer Science, Master of Science - MSc (Ing), Mathematical Computer Science at Czech Technical University in Prague, Faculty of Nuclear Sciences and Physical Engineering
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Université Paris-Est
Contributions:2 releases, 144 commits, 5 PRs in 4 years 3 months
nanoporesimulationsimulatoroxford-nanoporeoxford
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