Dimitrios Kartsaklis
Head Of Applied Quantum NLP Research at Cambridge Quantum
Cambridge, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolDimitrios Kartsaklis is a computational linguist and head of Applied Quantum NLP research with a DPhil from Oxford and eight years leading quantum language modelling teams at Cambridge Quantum/Quantinuum. He blends deep theoretical expertise in category-theoretic compositional semantics with hands-on NLP engineering experience from Apple’s Siri team and a prior 15-year software engineering career. Dimitrios has bridged academia and industry across Oxford, Cambridge, Queen Mary and Apple, publishing and teaching advanced topics while also contributing practical documentation improvements to open-source Quantum NLP tooling such as lambeq. Fluent in both research and product contexts, he focuses on distributional semantics, knowledge representation, and the intersection of ML and quantum computing for language tasks. An oft-overlooked strength is his longtime background in technical translation and editorial work, which honed his ability to communicate complex ideas clearly to diverse audiences.
8 years of coding experience
22 years of employment as a software developer
MSc, Artificial Intelligence, MSc, Artificial Intelligence at The University of EdinburghDPhil, Computer Science, DPhil, Computer Science at University of OxfordBSc(Hons), Computer Science, BSc(Hons), Computer Science at The Open University
Greek, English
Github Skills (4)
restructuredtext10
rs10
documentation10
python9
Programming languages (4)
Github contributions (5)
CQCL/lambeq
Oct 2021 - Dec 2021
A high-level Python library for Quantum Natural Language Processing
Role in this project:
Technical Writer
Technical WriterContributions:81 reviews, 21 commits, 29 PRs in 2 months
Contributions summary:Dimitrios primarily contributed to the repository by updating and improving the documentation. Their commits involved enhancing installation instructions, adding warnings for Windows users, and converting tutorials to a new format. Furthermore, the user added a CONTRIBUTING file with guidelines for contributing to the project and created release notes to provide information on software updates.
python-librarypythonquantum-computinglanguage-processinghigh-level
dimkart/lambeq-docs
Aug 2024 - Mar 2025
User manual and example notebooks for the lambeq QNLP library
Contributions:37 pushes, 9 branches in 6 months
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