Kimmo Sirén
Co-Founder at Orb
Helsinki, Finland
Summary
👤
Senior🎓
Top SchoolKimmo Sirén is a co-founder and computational scientist with 8 years of experience turning raw multi-omics data into actionable insights using deep learning, machine learning and bespoke pipelines. He blends a formal background in mathematics and a PhD in chemistry with domain expertise in (meta-)genomics, transcriptomics and metabolomics to profile microbial interactions across food production environments. At Orb and during a postdoc at the University of Copenhagen he built and applied DL/ML tools to discover bacterial guilds, phages and molecular links to sensory perception, often starting from untargeted GC‑MS and sequencing reads. Kimmo is comfortable “liking it raw”: he favors working directly with primary data and tensor-based feature extraction rather than overprocessed summaries. His training in viticulture and wine education brings a rare, application-focused perspective that bridges analytical rigor with real-world sensory outcomes.
8 years of coding experience
4 years of employment as a software developer
WSET level 4 Diploma, WSET level 4 Diploma at Wine & Spirit Education TrustMaster of Science - MS, Viticulture and Enology, Master of Science - MS, Viticulture and Enology at Montpellier SupAgroDoctor of Philosophy - PhD, Chemistry, Doctor of Philosophy - PhD, Chemistry at University of KaiserslauternMaster of Science - MS, Viticulture and Enology, Master of Science - MS, Viticulture and Enology at Hochschule Geisenheim UniversityBachelor of Science (BSc), Mathematics, Bachelor of Science (BSc), Mathematics at University of Helsinki
Github Skills (104)
social-media10
nmf9
windows9
blockchain9
vitest9
ethereum9
comparative-genomics9
population-genetics9
uniswap9
tailwindcss9
android9
metagenomics9
nlp8
crypto8
polygon8
Programming languages (8)
Github contributions (5)
kkpsiren/PlasmidNet
Oct 2021 - Feb 2024
Contributions:1 release, 1 PR, 2 pushes in 2 years 4 months
ku-cbd/PhageBoost
Jun 2020 - Nov 2020
Rapid discovery of novel prophages using biological feature engineering and machine learning
Contributions:1 release, 1 review, 34 commits in 4 months
prophagesmachine-learningdiscoveryrapidengineering
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