Amirpasha Mozaffari
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- Position: RESEARCH ENGINEER
- Earth Sciences - Earth Artificial Intelligence
- email: amirpasha [dot] mozaffari [at] bsc [dot] es
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Biography
I am a postdoctoral researcher in the Models and Workflows team (MWT) of the Computational Earth Sciences (CES) group at the Earth Science Department of the Barcelona Supercomputing Center (BSC-CNS). My specialization spans a range of Earth System modeling and the development of workflow management tools for effectively running scientific experiments, always adopting state-of-the-art software engineering techniques. Additionally, I contribute to the Climate Variability and Change (CVC) group, engaging in fundamental research to understand climate variability and change, climate extremes, and to develop new Earth System modeling capabilities, enhancing our ability to simulate and forecast climate variations.
My background in HPC workflows for ML applications in weather and climate modeling includes previous work at the Jülich Supercomputing Centre (JSC) on multiple European and national projects as a postdoctoral researcher in WarmWorld (01LK2203D), IntelliAQ (787576), Maelstrom (955513), and DeepRain (01IS18047A-E). I earned my PhD in Computational Geophysics from a joint program by Forschungszentrum Jülich and Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen.
Currently, I am focused on improving the performance of climate models on HPC systems for projects such as RESCUE (101056939), OptimESM (101081193), CDRESM (TED2021-130798B-I00), and developing ML solutions for enhancing land surface representations in climate models within the project CERISE (101082139).
My background in HPC workflows for ML applications in weather and climate modeling includes previous work at the Jülich Supercomputing Centre (JSC) on multiple European and national projects as a postdoctoral researcher in WarmWorld (01LK2203D), IntelliAQ (787576), Maelstrom (955513), and DeepRain (01IS18047A-E). I earned my PhD in Computational Geophysics from a joint program by Forschungszentrum Jülich and Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen.
Currently, I am focused on improving the performance of climate models on HPC systems for projects such as RESCUE (101056939), OptimESM (101081193), CDRESM (TED2021-130798B-I00), and developing ML solutions for enhancing land surface representations in climate models within the project CERISE (101082139).
Educación
- PhD (Dr. rer. nat.) in Computational Geosciences, Title: "Towards 3D Crosshole GPR Full-Waveform Inversion", RWTH Aachen, Germany
- MSc in Water Resource Engineering and Management, Dissertation title: "Effect of Borehole Design on Cross-Hole Electrical Impedance Tomography (EIT) Measurements", University of Stuttgart, Germany
Research
- Workflow
- Machine Learning (ML)
- High-Performance Computing (HPC)
- Geosciences
- Open Science
- Findable, Accessible, Interoperable, Findable (FAIR) Science