I'm a Ph.D. focused on Data Scientist, driven by the application of machine learning to data analysis and problem solving 📊. My work integrates experimental data science to extract actionable insights from complex datasets. During my PhD I worked in Seattle (Washington, USA), on a Fulbright Foundation scholarship for young researchers.
In this GitHub profile, you'll find projects combining general uses of machine learning, cheminformatics, and systems biology, including predictive modeling of antimycobacterial compounds, analysis of multi-omics datasets, and data-driven approaches for target identification in tuberculosis. I also develop general data science projects to strengthen end-to-end analytical and modeling workflows applicable to real-world problems.
🐍 Programming & Development Python · SQL
🔢 Data Processing & Analysis Pandas · NumPy · Jupyter Notebook · SciPy
📊 Data Visualization Matplotlib · Seaborn · Plotly · PowerBI
🤖 Machine Learning & Modeling Scikit-learn · XGBoost · TensorFlow (basics) · SHAP · statistical learning methods
🧪 Bioinformatics & Cheminformatics RDKit · Biopython · molecular descriptors & fingerprints · omics data analysis · network biology
🦠 Domain Expertise Tuberculosis biology · drug discovery pipelines · target-based and phenotypic screening data · antimicrobial resistance mechanisms