Teaching

    EOSC 325 · Principles of Physical Hydrogeology

    I focus on developing self-explainable deep learning (DL) models, particularly in Earth Sciences. My research aims to demystify the black-box nature of machine learning models and enhance their physical realism. Additionally, I am interested in using interpretable DL models to extract insights from observational data. My Ph.D. thesis centers on creating process-based algorithms to make machine learning models more transparent and trustworthy.