Arthur Amalvy
Chercheur Postdoctoral at Institute of Information Science, Academia Sinica
Taiwan
Summary
🤩
Rockstar🎓
Top SchoolArthur Amalvy is a postdoctoral researcher in natural language processing with a decade of experience spanning academic research and industry R&D across Taiwan and France. Currently at Academia Sinica's Institute of Information Science, he brings deep expertise from a PhD in TAL (Traitement Automatique du Langage) and teaching-research roles at Avignon University. His background includes applied engineering work—porting development kits to the cloud and R&D for a publishing technology company—so he bridges theoretical models and production-focused implementations. Fluent in multilingual academic environments, he completed graduate studies in Taiwan and an engineering degree in France, which shapes his cross-cultural approach to collaboration. He maintains active code repositories (see also his GitLab) indicating ongoing hands-on development alongside his research. Colleagues would describe him as a researcher who consistently turns linguistic insight into practical software tools.
10 years of coding experience
Master en informatique, Master en informatique at 國立中央大學Diplôme d'ingénieur, Computer Science, Diplôme d'ingénieur, Computer Science at Université de Technologie de Belfort-MontbéliardDoctorat, Informatics, Doctorat, Informatics at Avignon Université
English, Chinese
Github Skills (80)
transformers10
webots10
python10
coreference-resolution10
deep-learning10
gemma10
glm10
multimodal10
audio10
transformer10
nlp10
natural-language-processing10
physics-engine10
pytorch10
machine-learning-models10
Programming languages (7)
Github contributions (5)
CompNet/Renard
Jun 2023 - May 2026
Relationship Extraction from NARrative Documents
Contributions:12 releases, 8 PRs, 197 pushes in 2 years 11 months
relationship-extractioncharacter-networkscoreference-resolutionnernetwork-extraction
CompNet/Grimbert
Sep 2023 - Feb 2026
Contributions:3 releases, 2 PRs, 29 pushes in 2 years 5 months
nlpnovelsspeaker-attribution
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