I'm a Biomedical Engineer with a strong background in artificial intelligence and its applications in the medical field. My work and research focus on leveraging deep learning, multimodal AI, and advanced computational techniques to solve clinical challenges and enhance healthcare solutions.

• 🎓 Pursuing MSc in Biomedical Engineering at the Technical University of Denmark with a focus on AI in healthcare.
• 📚 MSc in Artificial Intelligence (University of Alicante, GPA: 8.84/10).
• 🧠 Passionate about multimodal AI, computer vision, bioprocess simulation, and clinical data analysis.
• 🏆 Recognized with awards for innovation and digital transformation in healthcare and ICT projects.

• Data Science Intern @ Cultzyme (2024-2025)

  • Developed and optimized AI infrastructure.
  • Contributed to bioprocess simulation tool development for biotech applications.

• Research Assistant @ University of Alicante (2023)

  • Conducted research in computer vision and machine learning for clinical applications.

• GNN-based Tractography Segmentation (2024)

  • Developed a novel method using Graph Neural Networks and supervised contrastive learning to improve white matter fiber segmentation.
  • 🛠️ Technologies: Python, Torch Geometric, Docker.

• Response Retrieval with RAG (2024)

  • Implemented a system using Retrieval-Augmented Generation with LLMs for enhanced response precision.
  • 🛠️ Technologies: Python, HuggingFace, PyTorch, Docker.

• 3D Brain Tract Segmentation (2023)

  • Designed a volumetric segmentation method using 3D convolutional networks to map neural connections.
  • 🛠️ Technologies: TensorFlow, PyTorch, Dipy, Slicer 3D.

• Fundeun Award (2024): Best ICT Project for "BrainNext Labs."
• UAEmpende Award (2024): Best Final Degree Project with business applications.
• Digital Transformation Award (2023): Innovative tools for clinical digital transformation.

• 📧 Email: [email protected]
• 🌐 LinkedIn
• 🖥️ GitHub

I'm a Biomedical Engineer with a strong background in artificial intelligence and its applications in the medical field. My work and research focus on leveraging deep learning, multimodal AI, and advanced computational techniques to solve clinical challenges and enhance healthcare solutions.

• 🎓 Pursuing MSc in Biomedical Engineering at the Technical University of Denmark with a focus on AI in healthcare.
• 📚 MSc in Artificial Intelligence (University of Alicante, GPA: 8.84/10).
• 🧠 Passionate about multimodal AI, computer vision, bioprocess simulation, and clinical data analysis.
• 🏆 Recognized with awards for innovation and digital transformation in healthcare and ICT projects.

• Data Science Intern @ Cultzyme (2024-2025)

  • Developed and optimized AI infrastructure.
  • Contributed to bioprocess simulation tool development for biotech applications.

• Research Assistant @ University of Alicante (2023)

  • Conducted research in computer vision and machine learning for clinical applications.

• GNN-based Tractography Segmentation (2024)

  • Developed a novel method using Graph Neural Networks and supervised contrastive learning to improve white matter fiber segmentation.
  • 🛠️ Technologies: Python, Torch Geometric, Docker.

• Response Retrieval with RAG (2024)

  • Implemented a system using Retrieval-Augmented Generation with LLMs for enhanced response precision.
  • 🛠️ Technologies: Python, HuggingFace, PyTorch, Docker.

• 3D Brain Tract Segmentation (2023)

  • Designed a volumetric segmentation method using 3D convolutional networks to map neural connections.
  • 🛠️ Technologies: TensorFlow, PyTorch, Dipy, Slicer 3D.

• Fundeun Award (2024): Best ICT Project for "BrainNext Labs."
• UAEmpende Award (2024): Best Final Degree Project with business applications.
• Digital Transformation Award (2023): Innovative tools for clinical digital transformation.

• 📧 Email: [email protected]
• 🌐 LinkedIn
• 🖥️ GitHub

Rocamora-García, P., Saval-Calvo, M., Villena-Martinez, V., Gallego, A.J. (2023). A Deep Approach for Volumetric Tractography Segmentation. In: Pertusa, A., Gallego, A.J., Sánchez, J.A., Domingues, I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2023. Lecture Notes in Computer Science, vol 14062. Springer, Cham. https://doi.org/10.1007/978-3-031-36616-1_46