Joaquìn Salva

At Business Meets Culture, I built visual reports to support strategic decision-making, optimized data-handling processes, and developed solutions to reduce repetitive tasks.

In my machine learning projects, I classified brain images to distinguish patients with schizophrenia, bipolar disorder, and healthy controls using SVM, Random Forest, KNN, Ridge, and Stacking models.

I also worked on supervised gene-expression classification for diagnosis. My final SVM model with an RBF kernel achieved an AUC-ROC of 0.93 after optimization with Grid Search and Cross Validation.

I build predictive models with Python, SQL, and R for classification, regression, and data analysis. I’m interested in applying artificial intelligence and data science to complex problems in health, biology, and business.