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Hey!

As a researcher in Artificial Intelligence, I focus on Natural Language Processing (NLP) and Data Science. My work involves using Large Language Models (LLMs) for converting natural language into structured query languages to enhance specialized knowledge domain question-and-answer systems.

I also contribute to Neural Information Retrieval by developing semantic search engines that integrate exact match and semantic similarity methods for improved information retrieval. Additionally, my research includes advancing long text analysis, few-shot/zero-shot document classification, and exploring novel NLP tasks, with a keen interest in retrieval-augmented language models.

My research endeavors aim to contribute to AI and computational science through innovative and practical solutions, encompassing ontologies, semantic web, and knowledge graph integration in AI systems.

Julio C. Rangel's Projects

dgl-ke icon dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

flair icon flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

obonet icon obonet

OBO-formatted ontologies → networkx (Python 3)

transformers icon transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

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