Education
Academic background across computer science, high performance computing, and applied AI, complemented by industry certifications in deep learning and agentic systems.
Academic
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PhD
PhD in Computer Science
University of A Coruña
2021 – PresentResearch focused on artificial intelligence and computer vision applications in real-time environments.
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Master
Master in High Performance Computing
University of A Coruña
2019 – 2021Specialized in parallel computing, optimization techniques, and high-performance software development.
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Bachelor
Computer Engineering
University of A Coruña
2015 – 2019Core computer science fundamentals, software engineering, and systems architecture.
Courses & Certifications
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Building with the Claude API
Built production-ready applications with the Claude API: messages, tool use, streaming, and patterns for reliable integration in real workflows.
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Introduction to Model Context Protocol
Covered Model Context Protocol (MCP) fundamentals with Anthropic Claude: connecting tools and data sources to agents, structuring context exchange, and building practical MCP integrations.
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Introduction to subagents
Covered subagent fundamentals with Anthropic Claude: designing specialized agents, coordinating multi-agent workflows, and applying AI agent patterns in practical development scenarios.
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Introduction to agent skills
Covered how to build and use Claude Skills: structuring reusable agent capabilities, integrating them into workflows, and applying them effectively in production-oriented scenarios.
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Claude Code 101
Covered Claude Code fundamentals: setup, core workflows, and practical use of Anthropic's agentic coding environment for day-to-day development tasks.
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Claude 101
Covered Claude fundamentals: capabilities, prompting, safe and effective use, and how to get strong results from the product.
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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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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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Deep Research with LangGraph
Capstone deep research: planning, web search, citations, iterative refinement with LangGraph.
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Building Ambient Agents with LangGraph
Built ambient agents with LangGraph: state graphs, tools, memory, and multi-agent patterns.
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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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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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Fundamentals of Deep Learning
Learned about neural networks, backpropagation, and optimization techniques. Implemented CNNs and RNNs in TensorFlow/Keras.
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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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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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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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Ordered Data Structures
Constructed hierarchical structures (heaps, B-trees) and graph algorithms (Dijkstra, BFS/DFS). Optimized memory allocation patterns.
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