I'm an Industrial Electronics and Automation Engineer graduated from the Polytechnic University of Valencia, and I hold a Master's in Artificial Intelligence from the International University of La Rioja. Currently, I work as an AI Engineer at HI Iberia, where I develop innovative solutions using machine learning and deep learning to tackle complex challenges, such as detecting anomalies in offshore wind platforms and land change detection with satellite image analysis.

I also have experience in developing virtual reality tools at Simumatik, where I contributed to the creation of virtual industrial commissioning environments. I had the opportunity to complete my final degree project with this company, which you can check out here Virtual Commissioning with Virtual Reality.

Throughout my career, I've worked in cybersecurity, which has allowed me to effectively integrate data, AI, and security knowledge to optimize decision-making in increasingly complex digital environments.

• Artificial Intelligence & Machine Learning:

  • Proficient in building models using Deep Learning, Transformers, RNN, and LSTM for tasks ranging from sequence modeling to object detection.
  • Extensive experience in developing and optimizing machine learning pipelines for various applications, including anomaly detection, classification, and regression.

• Land Change Detection in satellite images:

  • Specialized in detecting land changes in satellite imagery and environmental data using the state of the art in computer vision techniques.

• Data Science:

  • Skilled in statistical analysis, data preprocessing, and feature engineering to prepare datasets for robust model development.
  • Expertise in model evaluation, performance optimization, and using frameworks like scikit-learn, TensorFlow, and PyTorch to create high-performing predictive models.

• Marine Platforms:

  • Experience in developing models for monitoring and anomaly detection in offshore wind farms using sensor data and dynamics simulations.
  • Utilized surrogate models to simulate marine environments and detect faults or anomalies in complex marine systems.
  • Developed systems for real-time anomaly detection in offshore wind farms and other marine platforms, ensuring operational efficiency and predictive maintenance.

• Programming Languages:

  • Proficient in Python, MATLAB, and C++ for designing algorithms, data analysis, and implementing AI models.
  • Python expertise includes popular libraries such as NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch.

• Open-Source Systems (Linux):

  • Advanced knowledge of Linux operating systems for development, deployment, and system administration tasks.
  • Experience in using Linux for creating automated workflows, running AI models on high-performance systems, and managing cloud or local development environments.

• Containerization & Orchestration:

  • Docker: Proficient in using Docker to create containerized applications for AI/ML models, ensuring consistency across different environments.
  • Kubernetes: Experience in orchestrating containerized applications using Kubernetes, deploying scalable and resilient AI systems in distributed environments.
  • Implemented CI/CD pipelines with Docker and Kubernetes to streamline development and deployment processes for machine learning models.

I am currently working as an AI Engineer for HI Ibiera, where I develop and deploy advanced algorithms for satellite image analysis and offshore platform monitoring. My role involves improving the detection of terrain changes and identifying potential anomalies in marine wind farms.

• Building intelligent systems for anomaly detection in satellite images.
• Exploring new applications of Transformers in sequential data modeling.
• Creating datasets and models for marine environmental monitoring.
• Diving into LLM to create a very light version of ChatGPT to develop understanding on the topic

• Virtual Commissioning with Virtual Reality: Developed tools in Virtual Reality to simulate and optimize industrial commissioning processes at Simumatik.
• [Satellite Image Analysis for Anomaly Detection]: Built models using deep learning techniques to detect anomalies in satellite images for land change monitoring.

• [Customer Churn Prediction]: Developed a machine learning model to predict customer churn using Python, scikit-learn, and Pandas during my Ironhack Bootcamp.
• [Sales Forecasting Project]: Created a forecasting model using time-series analysis to predict sales trends.
• [Movie Recommendation System]: Built a recommendation system using collaborative filtering and content-based filtering for a streaming service dataset.

• [Marine Wind Platform Anomaly Detection]: Developed an anomaly detection system using sensor data from marine wind platforms to detect operational issues.
• [Image Classification with CNNs]: Built a Convolutional Neural Network (CNN) to classify images from the CIFAR-10 dataset.
• [NLP Sentiment Analysis]: Applied NLP techniques to analyze and predict the sentiment of movie reviews.

Feel free to reach out through.