Leonardo Bagaglini

Ph.D. in Mathematics working in the Earth Observation sector. I graduated in Mathematics in 2014 and I earned the doctoral degree in 2017. After the doctoral studies, I earned a post-graduate degree in Meteorology and Physical Oceanography, working on the eddy detection in HF radar-derived surface currents. As research fellow at the University of Bologna, I started to develop machine learning algorithms for remote sensing applications, focusing on GNSS time-series analysis. Then, I became a post-doctoral researcher at the Institute of Atmospheric Sciences and Climate of the Italian National Research Council, where I worked on the satellite passive microwave precipitation retrieval via machine learning algorithms.

Remote Sensing, Earth Observations, Machine Learning

The Passive Microwave Neural Network Precipitation Retrieval Algorithm for Climate Applications (PNPR-CLIM): Design and Verification. Bagaglini, L., Sanò, P., Casella, D., Cattani, E., Panegrossi, G. Remote Sens. 2021, 13, 1701. https://doi.org/10.3390/rs13091701.

Synoptic patterns and mesoscale precursors of Italian tornadoes. Bagaglini L., Ingrosso R., Miglietta M.M.. Atmospheric Research, 2021, 105503, ISSN 0169-8095. https://doi.org/10.1016/j.atmosres.2021.105503.

Characteristics of Extratropical Cyclones That Cause Tornadoes in Italy: A Preliminary Study. Tochimoto, E.; Miglietta, M.M.; Bagaglini, L.; Ingrosso, R.; Niino, H.. Atmosphere 2021, 12, 180. https://doi.org/10.3390/atmos12020180.

Development of a microwave-based precipitation climate data record for the Copernicus Climate Change. Service. Panegrossi, G., Sanò, P., Bagaglini, L., Casella, D., Cattani, E., Konrad, H., Niedorf, A., Schröder, M., Mikalsen, A. C., and Hollmann, R. EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18636, https://doi.org/10.5194/egusphere-egu2020-18636.

Towards a climate data record of precipitation through merging satellite observations by passive microwave sounders and imagers. H. Konrad, G. Panegrossi, A. Nedorf, P. Sanò, L. Bagaglini, M. Shröder, E. Cattani, A. C. Mikalsen, N. Selbach, R. Hollmann. The 22th international TOVS Study Conference, Quebec, Nov. 2019.

Eddy Detection in HF Radar-Derived Surface Currents in the Gulf of Naples. Bagaglini, L.; Falco, P.; Zambianchi, E., Remote Sens. 2020, 12, 97. https://doi.org/10.3390/rs12010097.

The energy functional of G2-structures compatible with a background metric, L. Bagaglini, Journal of Geometric Analysis. 2019. https://doi.org/10.1007/s12220-019-00264-6.

Nilmanifolds, submanifolds and flows related to classes of G2-structures, L. Bagaglini, Doctoral Thesis. Università degli Studi di Firenze.

Non orientable three-submanifolds of G2−manifolds, L. Bagaglini, Advances in Geometry, Volume 19, Issue 3, Pages 401–414, ISSN (Online) 1615-7168, ISSN (Print) 1615-715X, https://www.degruyter.com/view/j/advgeom.2019.19.issue-3/advgeom-2018-0023.

The Laplacian co-flow on almost abelian Lie groups, L. Bagaglini and A. Fino, Annali di Matematica (2018) 30(1), pp. 109-128. https://doi.org/10.1007/s10231-018-0753-9.

Laplacian co-flow on the Heisenberg group, L. Bagaglini, A. Fino and M. Fernández. Asian Journal of Mathematics. Volume 24 (2020), 2, 331 – 354. https://dx.doi.org/10.4310/AJM.2020.v24.n2.a7.

Coclosed G2-structures inducing nilsolitons, L. Bagaglini, A. Fino and M. Fernández, Forum Mathematicum (2018) 30(1): 109–128 https://doi.org/10.1515/forum-2016-0238.