Hugo Abonizio is a research scientist and machine learning engineer with 11 years of experience building and deploying neural models for search, ranking, and large language models on GPU and TPU clusters. Currently at Maritaca AI and previously at NeuralMind, he has improved ecommerce and general search pipelines using state-of-the-art Transformers and published in SIGIR and COLING. He combines academic depth—holding a PhD in Computer Engineering and a Master's in Computer Science—with hands-on production experience managing cloud infrastructure and deployment tooling. An active contributor to the prominent Hugging Face datasets hub, he has curated Portuguese datasets for hate speech and fake news detection, reflecting a strong focus on responsible NLP and data quality. Earlier roles span chatbot development for COVID-19 fact-checking, backend engineering, and teaching, showing a mix of research, product delivery, and mentorship. Hugo uniquely bridges large-scale model training and meticulous dataset curation to drive practical, high-impact NLP systems.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Universidade Estadual de Londrina
Master's degree, Computer Science, Master's degree, Computer Science at UEL - Universidade Estadual de Londrina
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Universidade Estadual de Campinas
🤗 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
Contributions:2 reviews, 5 commits, 5 PRs in 1 day
Contributions summary:Hugo primarily contributes to the addition and modification of datasets within the Hugging Face datasets repository. Their work involves integrating new datasets, specifically those related to hate speech and fake news detection in Portuguese. This includes implementing dataset loading scripts, fixing feature issues, and ensuring proper data formatting, reflecting a focus on natural language processing and dataset curation. The user has addressed issues related to label types and ordering.
Contributions:10 releases, 61 reviews, 36 PRs in 1 year 6 months
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