On Using Clustering for the Optimization of Hydrological Simulations. - Elnaz Azmi (ICDM Workshops, 2018)

Clustering as Approximation Method to Optimize Hydrological Simulations. - Elnaz Azmi; Uwe Ehret; Jörg Meyer 001; Rik van Pruijssen; Achim Streit; Marcus Strobl (Euro-Par, 2019)

Evolutionary Approach of Clustering to Optimize Hydrological Simulations. - Elnaz Azmi; Marcus Strobl; Rik van Pruijssen; Uwe Ehret; Jörg Meyer 001; Achim Streit (ICCSA (1), 2020)

Approximation and Optimization of Global Environmental Simulations with Neural Networks. - Elnaz Azmi; Jörg Meyer 001; Marcus Strobl; Michael Weimer; Achim Streit (PASC, 2023)

Approximation and Optimization of Compute-Intensive Environmental Simulations through Machine Learning Methods - Elnaz Azmi (2024)

iMagine: AI-Powered Image Data Analysis in Aquatic Science. - Elnaz Azmi; Khadijeh Alibabaei; Valentin Kozlov; Álvaro López García; Dick Schaap; Gergely Sipos (PASC, 2025)

Best practices for AI-based image analysis applications in aquatic sciences: The iMagine case study. - Elnaz Azmi; Khadijeh Alibabaei; Valentin Kozlov; Tjerk Krijger; Gabriele Accarino; Sakina-Dorothée Ayata; Amanda Calatrava; Marco M. De Carlo; Decrop Wout; Donatello Elia; Sandro Fiore; Marco Francescangeli; et al. (Ecol. Informatics, 2025)