Panagiotis Antoniadis
PHD Fellow at Københavns Universitet - University of Copenhagen
Copenhagen, Capital Region of Denmark
Summary
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Senior🎓
Top SchoolPanagiotis Antoniadis is an ELLIS PhD Fellow in Machine Learning at the University of Copenhagen with eight years of experience applying deep learning across biology and neurotech. He previously built generative models for single-cell transcriptomics and deep neural networks for EEG-based brain-computer interfaces at DeepLab, blending probabilistic modeling with applied signal processing. His background includes a 5-year integrated BSc/MSc in Electrical and Computer Engineering from NTUA and thesis work in visual emotion recognition, reflecting a strong foundation in computer vision. Alongside research, he has contributed technical writing and hiring leadership at Baeldung, showing an ability to communicate complex ML ideas to broader audiences. Notably, his trajectory bridges academic rigor and product-minded engineering, making him adept at turning cutting-edge models into usable tools for biological and neural data.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at Københavns Universitet - University of Copenhagen5-year joint BSc & MSc degree Electrical and Computer Engineering, 5-year joint BSc & MSc degree Electrical and Computer Engineering at National Technical University of Athens
English, German
Stackoverflow
108reputation
2kreached
7answers
1question
Github Skills (59)
python10
machine-learning10
flask-application10
proof-of-work10
gpu10
dictation10
mongodb10
adaptation10
language-processing9
numpy9
openfst9
attention-mechanism9
language-model9
neural-network9
deep-learning9
Programming languages (4)
Github contributions (5)
PanosAntoniadis/computer_vision-ntua
Mar 2019 - Jul 2019
Contributions:49 commits, 2 pushes in 3 months
PanosAntoniadis/emotion-gcn
Aug 2021 - May 2022
[IEEE FG 2021] Official implementation: Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition
Contributions:19 commits, 5 pushes, 8 comments in 9 months
facial-expression-recognitiongraph-convolutional-networks
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