Christos Christodoulopoulos
Principal Technology Adviser at Information Commissioner's Office
City of Edinburgh, Scotland, United Kingdom
Summary
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Senior🎓
Top SchoolChristos Christodoulopoulos is a Principal Technology Adviser based in Edinburgh with 11 years of experience bridging cutting-edge ML research and practical NLP systems. His career spans academic foundations—a PhD and postdoc focused on unsupervised grammar induction and semantic role labeling—to industry research roles at Amazon where he advanced applied language understanding. He specializes in Responsible AI, blending machine learning with linguistic and philosophical insights to build systems that are both effective and ethically grounded. An active contributor to CogComp’s widely used NLP libraries, he’s shipped backend features such as comma-resolution classifiers and robust data readers that improve parsing reliability. Known for turning deep research into production-ready components, he brings rare fluency across theory, engineering, and policy-facing technology advising at the ICO.
11 years of coding experience
12 years of employment as a software developer
MSc, Artificial Intelligence, MSc, Artificial Intelligence at The University of EdinburghBS, Technology Education and Digital Systems, BS, Technology Education and Digital Systems at University of Piraeus
English, Greek, French
Github Skills (4)
natural-language-processing10
java10
javas10
machine-learning8
Programming languages (5)
Github contributions (5)
CogComp/cogcomp-nlp
Oct 2014 - May 2017
CogComp's Natural Language Processing Libraries and Demos: Modules include lemmatizer, ner, pos, prep-srl, quantifier, question type, relation-extraction, similarity, temporal normalizer, tokenizer, transliteration, verb-sense, and more.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:186 commits, 22 PRs, 14 pushes in 2 years 7 months
Contributions summary:Christos contributed to the `cogcomp-nlp` repository, focusing on the development of features for comma resolution. Their work involved adding a LBJava classifier, implementing the `CommaReader` and `Comma` classes to handle data, and adding a train/test split. They fixed various bugs in the `Reader` to facilitate the accurate processing of data.
ellipsisverbextractionnatural-language-understandingpos-tagging
christos-c/bmmm
Jan 2015 - May 2022
The Bayesian Multinomial Mixture Model code from my 2011 paper (and thesis)
Contributions:1 release, 23 commits, 2 PRs in 7 years 5 months
thesismultinomialbayesianmixturemixture-model
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