About

I graduated in Computer Engineering from the University of Murcia in 2021, and completed a Master's degree the following year, deepening my expertise in data-driven methods and machine learning applied to complex real-world systems.

Since November 2024, I am a PhD Student in Computer Science at the University of Murcia (Department of Information and Communication Engineering), under the research line Knowledge Acquisition through Artificial Intelligence Techniques for Sustainable Environments. My doctoral work focuses on the application of machine learning and deep learning techniques to environmental monitoring, combining data from heterogeneous sources such as IoT sensors and satellite imagery to address real-world sustainability challenges. Alongside my doctoral research, I serve as an Associate Professor in the same department, contributing to undergraduate and postgraduate teaching in computer science and artificial intelligence.

I have participated in national research and innovation projects in areas such as precision agriculture, smart monitoring, and environmental data analysis, collaborating with both academic institutions and industry partners. In 2026, I completed a research stay at IBM Research Europe in Dublin, Ireland, where I gained experience in applied AI research in an international industrial environment.

Research Interests

  • Machine Learning & Deep Learning (PyTorch, TensorFlow, scikit-learn)
  • Remote Sensing & Satellite Image Analysis (Sentinel-2, Copernicus)
  • Environmental Monitoring — Water Quality, Desertification, Soil Moisture
  • Agricultural AI — Crop Disease Classification, Forest Inventory
  • Federated Learning

Education

  • PhD in Computer Science University of Murcia — Nov 2024 – present Dept. of Information & Communication Engineering

Publications

  1. Deep Learning for Soil Moisture Estimation: Fusing Satellite Data with Optimally-Lagged Meteorological Features

    A Martínez-Ibarra, A González-Vidal, A Cánovas-Rodríguez, AF Skarmeta

    arXiv preprint arXiv:2606.21475 — 2026

    arXiv DOI

  2. Attention Mechanisms and Transfer Learning for Robust Peach Leaf Damage Classification Under Domain Shift

    A Martínez-Ibarra, A Cánovas-Rodríguez, A González-Vidal, AF Skarmeta

    arXiv preprint arXiv:2606.02045 — 2026

    arXiv DOI

  3. Chlorophyll-a Mapping and Prediction in the Mar Menor Lagoon Using C2RCC-Processed Sentinel-2 Imagery

    A Martínez-Ibarra, A González-Vidal, A Cánovas-Rodríguez, AF Skarmeta

    arXiv / Zenodo — 2026

    arXiv DOI

Portfolio

turbidity_satellite_estimation

Mar Menor Lagoon surface turbidity estimation and analysis using Sentinel-2 satellite imagery.

JupyterSentinel-2Water Quality

peach-leaf-cbam

Attention-enhanced CNNs (CBAM) for agricultural leaf damage classification under domain shift conditions.

PyTorchCBAMComputer Vision

ForestAnnotationRefinement

Evaluates the impact of manual annotation refinement on instance segmentation accuracy for forest inventory systems.

JupyterSegmentationForestry

sat-img-download

Downloads, cloud-masks, and crops imagery from the Copernicus Data Space Ecosystem.

JupyterCopernicusSentinel-2

evaluation_desertification

Desertification assessment using remote sensing data and machine learning techniques.

JupyterRemote SensingML

Template-TF-FIUM

LaTeX thesis template for the Faculty of Computer Science (FIUM) at the University of Murcia.

LaTeXTemplateAcademic

Curriculum Vitae

Download my latest CV or view it directly in your browser.

Download CV (PDF)