Kleanthi Georgala is a Principal Software Developer (ML) with a decade of experience applying machine learning and scalable link discovery to real-world problems across telecommunications, healthcare, and smart cities. She holds a PhD (Summa Cum Laude) focused on time-efficient Link Discovery and has driven research-to-production work in EU-funded projects like HOBBIT, LIMES and SAKE. Her background spans academic research and industry roles—designing benchmarks for streamed data, building temporal-linking methods, and delivering forecasting and customer-insight solutions at companies such as Nokia, MSD and Intracom Telecom. Kleanthi blends deep expertise in record linkage, semantic web, and text mining with practical engineering skills for deploying ML systems under time and space constraints. Fluent in both research publication and product delivery, she has a track record of turning complex entity-matching research into performant tools used in enterprise and government contexts. Based in Athens, she brings an unusual combination of theoretical rigor and hands-on systems design that speeds up linking and inference on large, messy datasets.
10 years of coding experience
8 years of employment as a software developer
Master of Science (MSc), Artificial Intelligence, Master of Science (MSc), Artificial Intelligence at The University of Edinburgh
Bachelor of Science (BSc) - 4 years, Informatics and Telecommunications, 8/10, Bachelor of Science (BSc) - 4 years, Informatics and Telecommunications, 8/10 at University of Athens
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Leipzig University and University of Paderborn
Contributions:6 releases, 87 commits, 23 PRs in 3 years 3 months
pythonsemanticssemantic-weblinkrecord-linkage
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