This dual methodological framework — combining machine learning for predictive feature selection with multilevel modeling for statistical inference — provides a comprehensive lens on vaccine hesitancy across Sub-Saharan Africa. The findings highlight both individual-level drivers (linguistic and civic integration, trust networks, lived service experience) and structural country-level factors, offering empirically grounded targets for context-aware public health interventions.

A model for the square root of BMI on the Belgian Health Interview Survey (BHIS) data set `bmi_voeg`, using as covariates the General Health Questionnaire score (GHQ), GP contact (SGP), and the demographic and socio-economic variables age, sex, smoking, education, and income. The modelisation takes into account the BHIS's design into account

Rare Disease Atlas (Notre Dame summer research)

Big-Data ML project — Hate Speech & Topic Structure of r/MensRights (KU Leuven, "Collecting & Analyzing Big Data", Jan 2026, group of 4) Graduate-level supervised ML + NLP pipeline in R (quanteda, quanteda.textmodels, topicmodels, mallet, LDAvis, caret, glmnet, pROC). Full workflow: EDA & preprocessing, tokenization, collocations, word frequencies; manual annotation with inter-coder reliability; trained & compared Naive Bayes, Logistic Regression, Random Forest with hyperparameter tuning & cross-validation; evaluation via confusion matrix, precision/recall, F1, ROC/AUC; error analysis of false positives/negatives; applied best model to detect hate speech across the corpus. Topic modelling: LDA with coherence & exclusivity selection, topic interpretation, and topic frequency over time; TF-IDF. Includes a transparent "GenAI use" statement. Relevance: rigorous, reproducible supervised-ML + text-mining at master's level, incl. the annotation/reliability step that empirical text studies require.

As of July 20, 2026

R-based cleaning and analysis of the Google Play Store Apps dataset, with category-level insights for an ad-supported app business. Interactive Shiny dashboard linked separately.

Producto 1 del Portafolio Socioformativo de la asignatura Métodos de Investigación en Salud (MIN 26), Escuela de Medicina (UJMD). Presenta un mapa conceptual analítico-jerárquico elaborado en RMarkdown (DiagrammeR) que justifica el abordaje multiparadigmático —articulando el Positivismo (cuantitativo) y el Constructivismo (cualitativo)— frente al descontrol glucémico en Diabetes Mellitus Tipo 2 en El Salvador, integrando la evidencia científica con el humanismo clínico.