Daniel Danciu
CTO at Cradle Bio
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolDaniel Danciu is a CTO and engineering leader with 11+ years of experience translating research-grade algorithms into production-grade systems, currently steering Cradle Bio’s machine learning efforts to revolutionize protein design. He blends deep academic credentials—a PhD in genetic algorithms—with hands-on product engineering at Google where he helped kick off the technology behind Google Cast and scaled YouTube services to billions of devices. Previously he led multidisciplinary teams at Daedalean to build an autopilot capable of passing human pilot exams and at ETH Zürich worked on scaling Metagraph to index global DNA sequences. Daniel is equally comfortable designing models and writing low-level, production code that runs on thousands of servers and hundreds of millions of consumer devices. His career shows a recurring pattern: start from research, prototype across stacks and devices, then ship robust, audited systems to production. Based in Zurich, he combines scientific rigor with a penchant for delightful user experiences and end-to-end ownership.
11 years of coding experience
24 years of employment as a software developer
Colegiul Național de Informatică "Gr. Moisil” BrașovUniversitatea Babeș-Bolyai din Cluj-NapocaMaster of Science (MSc), Applied Mathematics, 10.00, Master of Science (MSc), Applied Mathematics, 10.00 at Universitatea Transilvania din Brașov
German, English, French, Hungarian, Romanian
Stackoverflow
143reputation
18kreached
3answers
2questions
Github Skills (143)
package-management10
extensible10
scalable10
bioconda10
graph10
conda10
bazel10
metagenomics10
assembly10
indexing10
bioinformatics10
intellij-plugin9
python9
intellij9
build-system9
Programming languages (9)
Github contributions (5)
ratschlab/secedo
Mar 2021 - May 2022
Master thesis for hanap
Contributions:8 releases, 470 commits, 13 PRs in 1 year 2 months
master-thesismasterthesis
leylabmpi/resmico
Jul 2021 - Dec 2022
Identifying misassemblies via deep learning
Contributions:1 release, 411 commits, 2 PRs in 1 year 5 months
pytorchmetagenomicsdeep-learningmetagenome-assemblymachine-learning
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