Nikolaos Stylianou
NLP Research Scientist at Omilia - Conversational Intelligence
Thessaloniki, Macedonia and Thrace, Greece
Summary
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Senior🎓
Top SchoolNikolaos Stylianou is an NLP Research Scientist with eight years of experience bridging academic research and applied conversational AI, currently working at Omilia and lecturing in Business Intelligence at Aristotle University of Thessaloniki. He holds a PhD in Computer Science from AUTH and an MSc in Big Data and Text Analytics from the University of Essex, with a research focus on language modelling and coreference resolution. His career includes postdoctoral work at CERTH and hands-on contributions within AUTH’s Intelligent Systems Lab, translating cutting-edge NLP methods into practical systems. Nikolaos combines deep theoretical knowledge with production-minded research, and his homepage documents a consistent record of publishing and tooling that supports reproducible language-model experiments. Based in Thessaloniki, he blends academic rigor with commercial conversational intelligence development, often working on tasks that improve contextual understanding in dialogue systems.
8 years of coding experience
5 years of employment as a software developer
Master’s Degree, Big Data and Text Analytics, Master’s Degree, Big Data and Text Analytics at University of EssexDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Aristotle University of Thessaloniki (AUTH)
Github Skills (28)
word-embeddings9
nlp8
simple-framework8
natural-language-processing8
sequence-labeling8
datasets8
language-processing8
speech8
evaluation7
pytorch7
named-entity-recognition7
machine-learning7
multiclass-classification7
computer-vision7
deep-learning6
Programming languages (2)
Github contributions (5)
nstylia/nstylia.github.io
May 2021 - Feb 2023
A beautiful, simple, clean, and responsive Jekyll theme for academics
Contributions:3 PRs, 43 pushes, 2 branches in 1 year 9 months
nstylia/pico_entities
Feb 2020 - Oct 2020
EBM+: Advancing Evidence-Based Medicine via two level automatic identification of Populations, Interventions, Outcomes in medical literature
Contributions:4 commits, 1 PR, 3 pushes in 7 months
ebmevidence-based-medicinemachine-learningliteratureinterventions
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