I am a Systems Engineering student passionate about transforming data into meaningful solutions through Machine Learning and Data Science. I thrive on the challenge of uncovering hidden patterns within complex datasets and developing intelligent systems that address real-world problems. My academic journey has equipped me with a strong foundation in programming, algorithms, and analytical thinking, while my hands-on projects have strengthened my skills in Python, data visualization, and predictive modeling. I am committed to continuous learning and eager to contribute my knowledge and creativity to innovative, data-driven solutions.
This is a selection of projects that showcase my learning journey across different areas of data science and engineering.
| Project | Brief Description | What I Learned |
|---|---|---|
| 💳 Credit Risk Analysis | An end-to-end data science project to predict loan default, covering data cleaning, EDA, and modeling. | How to execute a data science project from start to finish, from defining the business problem to evaluating the model. I applied the Medallion Architecture (Bronze, Silver, Gold) to manage and transform data in a structured and scalable way. |
| 🧬 Biomedical Multi-label Classification | An AI solution for automatic classification of biomedical literature using Transformer-based deep learning models, categorizing medical articles into areas such as cardiovascular, neurological, hepatorenal, and oncological. | How to build a multi-label text classifier end-to-end, applying BERT fine-tuning, tokenization, and NLP preprocessing. Explored alternative approaches with embeddings, classical ML models, and generative LLMs, achieving a Weighted F1-Score of ~92%. Also built an interactive dashboard for metrics visualization. |