I'm Álvaro, a data scientist with a strong specialization in Natural Language Processing (NLP), particularly in the application of Transformer-based architectures and Generative AI. My interest in NLP began during my undergraduate studies in Computer Science at UNED, where I became deeply engaged with the computational aspects of human language. To advance my knowledge, I enrolled in a research-oriented Master's degree in NLP at UNED, where I have worked extensively with state-of-the-art models using PyTorch and the Hugging Face Transformers library. I am currently completing my MSc thesis on Automatic Fake News Detection on Social Media, with a focus on evaluating the generalization capabilities of Transformer-based models across different topical domains. My work aims to bridge academic research and practical NLP applications, with a particular emphasis on robustness, transfer learning, and low-resource settings.
Master's degree in Natural Language Processing, ongoing
UNED University
Computer science
UNED University
A multithreaded news articles scraper based on Selenium. It persists and parses normal and reader mode webpages.
A multithreaded tweet scraper based on Selenium that persists tweet information without using the X (formerly Twitter) API.
Comparing classical Machine Learning models with Deep Learning techniques.
Evaluating different RNN architectures to address the Sentiment Analysis task.
Analysing trend words and topics of tweets related to COVID-19 desease and La Palma volcano eruption. Full report here