Kenneth Enevoldsen is an academic software engineer and researcher with nine years of experience building NLP and representation learning solutions for psychiatry, genetics, and narrative analysis. Based in Aarhus, he develops Scandinavian-language models and open-source tools such as DaCy, augmenty, textdescriptives and tomsup, bridging research code and production-ready NLP resources. His background spans a PhD in multimodal feature learning, postdoctoral research, and teaching practical ML and experimental methods, giving him a strong mix of applied research and pedagogy. Fluent in Python and R, he has a track record of democratizing tools for Danish-language processing and text anonymization, reflecting a pragmatic focus on reproducibility and usability.
9 years of coding experience
2 years of employment as a software developer
High School Mathematics (A) Social Science (A) Biology (B) og Health Science (B), High School Mathematics (A) Social Science (A) Biology (B) og Health Science (B) at Rønde Gymnasium
Doctor of Philosophy - PhD Multimodal Feature Learning for Decision Support Systems, Doctor of Philosophy - PhD Multimodal Feature Learning for Decision Support Systems at Aarhus University
spaCy-wrap is a wrapper library for spaCy for including fine-tuned transformers from Huggingface in your spaCy pipeline allowing you to include existing fine-tuned models within your SpaCy workflow.
Contributions:6 releases, 50 reviews, 130 commits in 11 months
A utility package handling Single Nucleotide polymorphism data in Python
Contributions:2 reviews, 34 PRs, 80 pushes in 11 months
polymorphismpythongeneticshandlingsnp
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