Education

Academic background across computer science, high performance computing, and applied AI, complemented by industry certifications in deep learning and agentic systems.

Academic

  • PhD

    PhD in Computer Science

    University of A Coruña

    University of A Coruña

    2021 – Present

    Research focused on artificial intelligence and computer vision applications in real-time environments.

  • Master

    Master in High Performance Computing

    University of A Coruña

    University of A Coruña

    2019 – 2021

    Specialized in parallel computing, optimization techniques, and high-performance software development.

  • Bachelor

    Computer Engineering

    University of A Coruña

    University of A Coruña

    2015 – 2019

    Core computer science fundamentals, software engineering, and systems architecture.

Courses & Certifications

12 courses

  • 2026 Anthropic Academy
    Anthropic Academy

    Claude 101

    Covered Claude fundamentals: capabilities, prompting, safe and effective use, and how to get strong results from the product.

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  • 2026 Anthropic Academy
    Anthropic Academy

    Claude Code in Action

    Applied Claude Code in real workflows: agentic coding patterns, tooling integration, and shipping reliable changes with AI-assisted development.

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  • 2025 LangChain Academy
    LangChain Academy

    Deep Agents with LangGraph

    Built deep agents with LangGraph for complex, long-running tasks, including to-do lists, file management, and sub-agent creation.

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  • 2025 LangChain Academy
    LangChain Academy

    Deep Research with LangGraph

    Capstone deep research: planning, web search, citations, iterative refinement with LangGraph.

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  • 2025 LangChain Academy
    LangChain Academy

    Building Ambient Agents with LangGraph

    Built ambient agents with LangGraph: state graphs, tools, memory, and multi-agent patterns.

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  • 2025 LangChain Academy
    LangChain Academy

    Foundation: Introduction to LangGraph

    Mastered LangGraph fundamentals: state and memory, human-in-the-loop workflows, long-term persistence, and deployment of reliable agents.

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  • 2022 Iterative
    Iterative

    Iterative Tools for Data Scientists and Analysts

    Learned about data version control, model training, and model evaluation. Used DVC/MLflow for workflow automation.

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  • 2022 Nvidia
    Nvidia

    Fundamentals of Deep Learning

    Learned about neural networks, backpropagation, and optimization techniques. Implemented CNNs and RNNs in TensorFlow/Keras.

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  • 2020 Coursera
    Coursera

    Introduction to Neural Networks and PyTorch

    Built neural networks with PyTorch, covering CNNs, RNNs, backpropagation, and activation functions. Applied to image classification and sequence modeling.

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  • 2020 Coursera
    Coursera

    Object-Oriented Data Structures in C++

    Implemented OOP data structures (linked lists, trees, hash tables) with complexity analysis in C++. Focused on memory management and recursive algorithms.

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  • 2020 Coursera
    Coursera

    Applied AI with Deep Learning

    Learned about deep learning models (GANs, LSTMs, autoencoders) using TensorFlow/Keras. Included model deployment via Flask APIs.

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  • 2020 Coursera
    Coursera

    Ordered Data Structures

    Constructed hierarchical structures (heaps, B-trees) and graph algorithms (Dijkstra, BFS/DFS). Optimized memory allocation patterns.

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