Ignacio Ojer García

PhD Student

Ignacio holds a Bachelor’s degree in Physics (2022) and a Master’s degree in Secondary Teaching Training (2023), both from the University of Zaragoza (Spain). He began his academic career as a research assistant within the Fluid Dynamic Technologies group, where he participated in several interdisciplinary projects involving computational modeling and data-driven analysis. Building on this experience, he is currently pursuing a PhD under the supervision of Adrián Navas-Montilla and Sergio Martínez-Aranda.

His research focuses on the development of computational models for geophysical phenomena, combining physically-based formulations with machine learning techniques to enhance predictive accuracy and parameter calibration. It emphasizes data assimilation approaches—such as satellite imagery and other remote sensing sources—to improve model inputs and validation, while leveraging AI-driven optimization strategies to address uncertainty and reduce computational cost. He is also interested in the effective representation and communication of simulation outcomes through interactive visualization tools, as well as in the development of GIS-based platforms to support spatial analysis. The core purpose is to build efficient, scalable modeling frameworks that inform risk assessment and mitigation strategies in the face of climate-driven natural hazards.