Jindra Helcl
Výzkumník at University of Oslo
Prague, Prague, Czechia
Summary
👤
Senior🎓
Top SchoolJindra Helcl is a computational linguist and researcher with a decade of experience building and evaluating language technologies, currently working on data curation and LLM evaluation at the University of Oslo while holding a postdoctoral role at Charles University. He brings hands-on machine translation engineering experience from contributions to the well-known Nematus TensorFlow toolkit, where he improved encoder/decoder depth and bidirectional merging to boost model performance. His background spans academia and industry — PhD in Computational Linguistics, research positions at Edinburgh and DFKI, and internships at Microsoft and Google — giving him a strong mix of theoretical rigor and production-minded engineering. Based in Prague, he blends deep technical skills in NLP and ML with practical software development from early roles in Java/C++ and web development. Colleagues describe him as detail-oriented in dataset curation and creative in evaluation design, with an unexpected home life shared with two cats that double as unofficial lab assistants.
10 years of coding experience
8 years of employment as a software developer
Mathematics and Physics, Mathematics and Physics at Gymnázium Christiana DoppleraBc., Computer Science, Bc., Computer Science at Univerzita Karlova v PrazeDoctor of Philosophy (Ph.D.), Computational Linguistics, Doctor of Philosophy (Ph.D.), Computational Linguistics at Ústav formální a aplikované lingvistiky, MFF UK
Czech, English, Slovenian, German
Stackoverflow
3,607reputation
1.1mreached
42answers
5questions
shell
top-5%
Github Skills (12)
sequence-to-sequence10
machine-translation10
deep-learning10
tensorflow10
python10
shell9
union-types6
type-checking6
javascript6
io6
annotations6
java6
Programming languages (8)
Github contributions (5)
EdinburghNLP/nematus
Feb 2017 - Feb 2017
Open-Source Neural Machine Translation in Tensorflow
Role in this project:
ML Engineer
ML EngineerContributions:9 commits in 9 days
Contributions summary:Jindra primarily contributed to the development of a neural machine translation system. Their work focused on enhancing the encoder and decoder architectures, introducing deep layers for improved performance. The user also added options for merging bidirectional layers and deep output layers, which directly impact the model's training and architecture. Additionally, they made minor changes related to domain interpolation and handling of white spaces, demonstrating iterative development.
machine-translationtranslationnmttensorflowsequence-to-sequence
ufal/neuralmonkey
Jan 2016 - Apr 2020
An open-source tool for sequence learning in NLP built on TensorFlow.
Contributions:8 releases, 1208 commits, 289 PRs in 4 years 4 months
nlpsequencepythonlanguage-modelingdeep-learning
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