Krzysztof Wróbel
NLP Expert at BIELIK.AI
Cracow Metropolitan Area Poland
Summary
👤
Senior🎓
Top SchoolKrzysztof Wróbel is an NLP expert with 13 years of experience combining academic research (PhD-level work and ongoing roles at Jagiellonian and AGH universities) with practical engineering across industry projects and startups. He designs and prototypes NLP solutions end-to-end—balancing resources, timelines and accuracy—and has contributed to popular open-source tooling such as flair (adding embeddings and model improvements). Skilled in transformers, RNNs, POS tagging, dependency parsing, NER, MT and hybrid rule/statistical approaches, he also supervises data annotation and assesses model quality for production use. Equally comfortable publishing research and competing in cryptography/logic contests, he brings a rigorously analytical mindset and a taste for challenging problems. Based in Cracow, he collaborates remotely or locally and co-authors projects like KRNNT, a Polish morphological tagger, reflecting deep specialization in Slavic-language processing.
13 years of coding experience
2 years of employment as a software developer
PhD Computer Science, PhD Computer Science at AGH University of Krakow
Polish, English, German
Github Skills (9)
pytorch10
machine-learning10
nlp10
python10
natural-language-processing10
word-embeddings9
sequence-labeling9
mask-rcnn9
faster-rcnn9
Programming languages (15)
Github contributions (5)
flairNLP/flair
Jan 2020 - Mar 2021
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 8 commits, 10 PRs in 1 year 2 months
Contributions summary:Krzysztof contributed to the flairnlp/flair repository by fixing typos, annotations and implementing new features related to the natural language processing framework. Their work includes modifying the `flair/embeddings.py` and `flair/models/sequence_tagger_model.py` files, suggesting improvements and bug fixes within the core logic of the model. They introduced a new document embedding type `DocumentCNNEmbeddings`, along with corresponding test implementations.
nlppytorchnamed-entity-recognitionartsemantic-role-labeling
namehash/ens-label-inspector
Sep 2023 - Dec 2024
Detailed inspection of labels in ENS names
Contributions:7 releases, 15 reviews, 40 PRs in 1 year 3 months
ens
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