🎓 Mathematician • 🧠 AI Enthusiast • 💻 Developer
📍 Based in Spain | 💡 Open to Research & Engineering Opportunities
I'm a Mathematics graduate with a Master’s in Big Data and a strong passion for Artificial Intelligence, particularly in Deep Learning and Reinforcement Learning.
Currently working as a Data Scientist Intern at NTT DATA, I enjoy building intelligent systems, learning from cutting-edge research, and solving real-world problems through code and models.
I'm particularly focused on:
- 🧠 Neural architectures for computer vision
- 🔁 Deep Reinforcement Learning
- 📊 Probabilistic modeling & statistical ML
- 🧪 Self-driven study of foundational resources
I’m currently working through the following core books and courses:
The Elements of Statistical Learning— Hastie, Tibshirani & FriedmanDeep Learning— BishopReinforcement Learning: An Introduction— Sutton & BartoDeep Generative Modeling— TomczakProbabilistic Machine Learning (Advanced Topics)— Kevin P. Murphy- TensorFlow for Deep Learning Bootcamp (Udemy)
| Project | Description | Link |
|---|---|---|
| Medical Image Segmentation (TFM) | Combining nn-UNet and deep RL to evaluate and improve segmentation in medical images autonomously. | Private |
| MSAN (NTT DATA) | Forecasting health care time series with exploratory analysis of data completeness and quality. | Private |
| SIGMA (NTT DATA) | Integrated system for IBsalut to manage health records more efficiently. | Private |
| Reinforcement Learning Exercises | Implementing algorithms and examples from Sutton & Barto’s book. | GitHub ↗ |
| TensorFlow Bootcamp Projects | Hands-on deep learning projects using TensorFlow. | GitHub ↗ |
| Microservices in Java | Two connected REST APIs with Spring Boot & Docker. | GitHub ↗ |
- Languages: Python, Java, R
- Libraries & Frameworks: TensorFlow, Scikit-learn, PyTorch, Pandas, SpringBoot
- Tools: Git, SQL, Docker, JIRA, Confluence
- ML Areas: Supervised Learning, Time Series, Computer Vision, RL
- Soft Skills: Logical thinking, autonomy, initiative, love for learning
🧠 My long-term goal is to contribute to meaningful AI research, and possibly pursue a PhD where math and machine learning meet.