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Sabbatical Giovanni Lapenta: Machine Learning for Turbulence and Reconnection

1) Develop a new capability of big data analytics to add to my expertise on simulation and theory. The mission magnetospheric multiscale (MMS) launched by NASA has a wealth of data with unprecedented accuracy: by visiting the teams at University of Colorado (CU) and at UCLA I can work with experts that have designed some of the on-borad experiments. Joining data analysis and simulation will give a boost to my research and to my teaching career. 2) A new mission launches in July: Parker Solar Probe (PSP) and another, Solar Orbiter (SO), will soon follow. I will work with the team of the senior observatory scientist of PSP (Velli at UCLA and JPL) to develop new expertise on the modelling of the solar wind under conditions observed by the missions. 3) I will immerge in a new activity that I worked to create in the past year: artificial intelligence (AI) and machine learning (ML) applied to space data. In the past year, I worked hard to develop this new direction, an effort that led to a new EC funded H2020 project: AIDA that I will coordinate starting in September. I will use part of the sabbatical to strengthen my expertise on AI and ML and to set the new AIDA project in the right direction. Experts at UCLA and CU will be valuable help, especially in the IGPP at UCLA where I already have contacts

Date:1 Feb 2023 →  Today
Keywords:machine learning, Magnetospheric MultiScale (MMS) and Parker Solar Probe (PSP) mission, geomagnetic storms
Disciplines:Astronomy and astrophysics, Machine learning and decision making