Jonatas Grosman
Professor at Pontifícia Universidade Católica do Rio de Janeiro
Rio de Janeiro, Brazil
Summary
🤩
Rockstar🎓
Top SchoolJonatas Grosman is a Brazilian computer scientist and professor with a PhD and over a decade of experience bridging academic research and practical software development. Based in Rio de Janeiro, he has contributed to major open-source NLP infrastructure—adding multiple Portuguese datasets to Hugging Face’s widely used datasets hub—demonstrating expertise in dataset engineering and multilingual NLP. At PUC-Rio he combines teaching and research roles since 2017, translating advanced ML research into reusable tools and classroom practice. His background spans research assistantships and industry-facing roles, including a venture partner stint, reflecting an ability to move between deep technical work and strategic initiatives. Curious and hands-on, he focuses on building useful, well-documented resources that enable others to reproduce and extend NLP experiments.
10 years of coding experience
3 years of employment as a software developer
Technologist, Information Systems, Technologist, Information Systems at Faculdade de Educação Tecnológica do Estado do Rio de JaneiroPontifical Catholic University of Rio de Janeiro
Portuguese, English
Stackoverflow
312reputation
40kreached
3answers
4questions
Github Skills (17)
python10
nlp10
machine-learning9
natural-language-processing9
pandas8
datasets8
pytorch7
tensorflow7
speech-recognition6
highcharts6
database6
huggingface-transformers6
huggingface-datasets6
jupyterlab6
eclipselink6
Programming languages (7)
Github contributions (5)
huggingface/datasets
Dec 2020 - Jan 2021
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Role in this project:
Data Scientist
Data ScientistContributions:7 reviews, 13 commits, 15 PRs in 1 month
Contributions summary:Jonatas contributed to the Hugging Face datasets repository by adding and modifying dataset scripts. They implemented new datasets, including LeNER-Br, ASSIN, ASSIN 2, BrWaC, Mac-Morpho, and HAREM. These contributions involved creating data loading and processing functionalities for diverse NLP tasks. The user also adjusted existing dataset features and updated dataset-related documentation.
ml-modelstensorflownatural-language-processingmanipulationdata-science
jonatasgrosman/asrecognition
Jul 2021 - Feb 2022
ASRecognition: just an easy-to-use library for Automatic Speech Recognition.
Contributions:3 releases, 17 commits, 8 pushes in 6 months
voice-recognitionasrspeech-to-textrecognitionctc
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