Gianvito Urgese

Associate Professor

Turin, Piedmont, Italy
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Summary

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Gianvito Urgese is an Associate Professor at Politecnico di Torino with a decade of experience bridging neuromorphic computing, bioinformatics, and Industry 4.0 systems. He leads the inNuCE Lab and coordinates national and EU projects (including EBRAINS-Italy and HBP), translating cutting-edge research into industrial R&D for smart infrastructure and embedded systems. His work spans designing task-specific algorithms and heterogeneous SW/HW accelerators for bioinformatics and embedded AIoT, and he has contributed documentation and tutorials to the well-known SeqAn bioinformatics library. A summa cum laude electrical engineer with a PhD focused on computational methods for bioinformatics and neuromorphic platforms, he teaches neuromorphic engineering, ML, and Python at graduate and PhD levels. Beyond publications in top journals, he serves on editorial boards and as a topic editor, combining deep technical design skills with hands-on system implementation across FPGA, GPGPU, and neuromorphic hardware.
code10 years of coding experience
job8 years of employment as a software developer
bookITIS "G. Giorgi" Brindisi
bookErasmus Student, Electrical engineering, Erasmus Student, Electrical engineering at České vysoké učení technické v Praze
bookMaster of Science (M.Sc.), Electrical Engineering, 110 summa cum laude, Master of Science (M.Sc.), Electrical Engineering, 110 summa cum laude at Politecnico di Torino
languagesItalian, English
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Github Skills (5)

text-align10
bioinformatics10
text-alignment10
documentation10
cpp8

Programming languages (6)

C++RShellHTMLJupyter NotebookPython

Github contributions (5)

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seqan/seqan

Mar 2016 - Oct 2016

SeqAn's official repository.
Role in this project:
userTechnical Writer
Contributions:10 commits, 5 PRs, 15 comments in 7 months
Contributions summary:Gianvito's commits primarily focus on documentation updates within the SeqAn repository. They created and revised tutorials, including those related to scoring schemes and pairwise sequence alignment, along with providing code examples. The updates include corrected references, descriptions of biological concepts, and improvements to the overall structure and clarity of the documentation. The user also added references for algorithms and extended descriptions within the documentation.
simdsequenceindexingsequence-alignmentsseqan
gurgese/seqan3

Mar 2017 - Mar 2018

Contributions:7 pushes in 11 months
apisequencec-librarybioinformaticsmodern-c
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