Filip Ilievski
Assistant Professor (Sr.) at Vrije Universiteit Amsterdam (VU Amsterdam)
Amsterdam, North Holland, Netherlands
Summary
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Senior🎓
Top SchoolFilip Ilievski is an Assistant Professor and senior research scientist with 11 years of experience at the intersection of knowledge graphs, commonsense reasoning, and information extraction. He has led machine commonsense projects at USC's Information Sciences Institute and returned to VU Amsterdam after a postdoc and a PhD focused on identifying long-tail entities in text. His work blends rigorous semantic web methods with practical NLP, including profiling unknown entities using human-like expectations to fill knowledge gaps. Filip has international research experience including a productive visiting stint at CMU and multiple scholarship-funded degrees, graduating his MSc cum laude. He also contributes to applied text-analysis teaching materials on GitHub, demonstrating a commitment to education and reproducible tooling. His profile shows a rare combination of deep semantic expertise and hands-on data-science practice that drives more trustworthy human–AI collaboration.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computational Linguistics Semantic Web Artificial Intelligence, Doctor of Philosophy - PhD Computational Linguistics Semantic Web Artificial Intelligence at Vrije Universiteit Amsterdam (VU Amsterdam)Bachelor of Science (B.Sc.) Informatics and Computer Engineering, Bachelor of Science (B.Sc.) Informatics and Computer Engineering at Faculty of Information Sciences and Computer Engineering (FINKI)Finished high school Natural Sciences and Mathematics, Finished high school Natural Sciences and Mathematics at Josip Broz Tito
English, Macedonian, Spanish, Dutch, serbocroatian
Github Skills (8)
functionfs10
python10
text-analysis10
data-structure9
jupyter-notebook9
data-structures9
file-handling8
nlp7
Programming languages (7)
Github contributions (5)
cltl/python-for-text-analysis
Nov 2017 - Jan 2018
If you want to use Python for text analysis, this course is for you!
Role in this project:
Data Scientist
Data ScientistContributions:33 commits, 23 pushes, 1 issue in 2 months
Contributions summary:Filip's contributions involve the creation and modification of an assignment notebook focused on functions and file handling in Python, particularly related to text analysis. The changes include the addition of new exercises, the implementation of text processing functions with specific tasks based on the input `task` variable, and the explanation of chosen data structures. This suggests the user is actively engaged in learning and applying Python for text-based data manipulation and analysis within the context of the course.
nlpnatural-language-processingpythonpython3
cltl/ELBaselines
Jun 2016 - Sep 2016
Contributions:34 commits, 34 pushes, 1 branch in 2 months
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