Colombian-Spanish student
exploring AI & data
I'm a third-year student at the University of London studying Data Science & Business Analytics, passionate about AI, machine learning, and turning data into meaningful insight.
Currently applying to master's programs for Fall 2026. I have hands-on experience as a Software Engineer and Data Scientist, working with AI/ML technologies and Large Language Models.
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Featured Projects
May 2026 - Present
ActiveStock Market Prediction & Evaluation Framework
A Python framework for registering, running, and comparing stock return prediction models across 24 algorithms and 7 model families. Supports multi-horizon forecasting (1, 5, and 21 days), classification and regression targets, walk-forward cross-validation, SHAP feature importance, macroeconomic feature enrichment via the FRED API, automated strategy optimisation, portfolio construction with four allocators, and realistic backtesting with transaction costs.
September 2024 - Present
Project NoCap: AI-Powered Fact-Checking for Instagram
An AI-powered fact-checking assistant for Instagram that helps users quickly assess the credibility of posts and reels. By forwarding content to the @project_nocap account, users receive an automated analysis that highlights potential misinformation, bias, and links to more reliable sources, making it easier to navigate the information overload on social media.
September 2025 - April 2026
Machine Learning Analysis of Diabetes-Related Health Outcomes (University of London Coursework)
A machine learning coursework project for ST3189 (Machine Learning) at the University of London, applying unsupervised learning, classification, and regression to the 2024 CDC Behavioral Risk Factor Surveillance System (BRFSS) - a telephone survey of 457,670 US adults. PCA and K-means clustering reveal interpretable health dimensions and identify a high-risk subgroup with 55% diabetic prevalence. Seven classifiers achieve AUC scores of 0.75-0.81 for predicting diabetes status without clinical tests, and gradient boosting predicts physical health burden among confirmed diabetics with R-squared = 0.45.
Open to opportunities
I'm always interested in discussing new projects, research collaborations, or internship opportunities.
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