I am a Biomedical Engineer passionate about bridging the gap between healthcare and artificial intelligence. Since graduating, I have been working as an Independent Researcher, dedicating my time to mastering Deep Learning architectures and solving complex problems in medical diagnostics.

My primary focus is building robust AI pipelines that translate raw medical data (DICOM, Signals) into actionable clinical insights.

My technical toolkit covers the entire machine learning lifecycle, from data preprocessing to model optimization:

Languages & Core:

Deep Learning & Machine Learning:

Medical Imaging & Vision:

Optimization & Data Science:

• 🩻 Medical Image Segmentation: Developing U-Net based architectures for precise tumor/organ segmentation in MRI and CT scans.
• 🎯 Model Optimization: Using Optuna for hyperparameter tuning to squeeze the best performance out of models.
• 📊 Ensemble Learning: Combining Deep Learning models with Gradient Boosting (XGBoost/CatBoost) for tabular medical data analysis.