Niccolò MAFFEZZOLI

Joint Chair between the University of Venice and the National Research Council, Institute of Polar Sciences.

Email: niccolo.maffezzoli@unive.it

- Ph.D., Geophysics, 2017, Niels Bohr Institute, University of Copenhagen.
- M.Sc., Physics with curriculum in nuclear and particle physics, 2014, University of Milano-Bicocca.

I received my master's degree in nuclear and particle physics from Milano-Bicocca University in 2014. My background ranges from applied particle physics to environmental radioactivity and high-energy physics. My M.Sc. thesis at the nuclear fission reactor in Pavia (Italy) introduced me to ice core science. During my PhD at the Niels Bohr Institute I worked on continuous flow analysis systems for past sea ice reconstructions from ice core records. I continued my research on climate reconstructions at the Niels Bohr Institute, at the Italian National Research Council and at the University of Venice until 2019. Between 2020 and 2022 I was Marie Curie Fellow at the University of Venice with a project on computer vision and machine learning applied to ice core analyses, partnered with the University of Bergen. In 2022-23 I worked on glacier modeling with machine learning in collaboration with the University of California, Irvine. From 2023-2025 I was Assistant Specialist at the University of California Irvine, and Marie Curie Fellow at the University of Venice, working on modeling the ice thickness of the Earth's glaciers.  

I am particularly interested in exploring, and developing machine learning models for various problems in Earth Science. At the moment (2025), I work on ice thickness inversion models of glaciers (ICEBOOST) and ice sheets, and grounding line identification from SAR differential interferometry.

Individual Funding and Fellowships

• MARIE CURIE GLOBAL FELLOWSHIP 2021, ”Estimating the ice volume of Earth’s glaciers via Artificial Intelligence and remote sensing, SKYNET”, University of Venice/University of California Irvine, EUR 288,000.
• CLIMATE CHANGE A.I. INNOVATION GRANT 2021, ”Estimate the ice volume of all glaciers in High Mountain Asia with deep learning, ICENET”, National Research Council, Institute of Polar Sciences/University of California Irvine, USD 145,000.
• MARIE CURIE EUROPEAN FELLOWSHIP 2018, ”Artificial Intelligence techniques for ice core analyses, ICELEARNING”, University of Venice/Unversity of Bergen, EUR 171,000.

Field expeditions

Greenland: Renland (2015), EGRIP (2016).
Svalbard: Ny-Alesund (2018, 2019, 2023).

Recent publications

- Maffezzoli, N., Rignot, E., Barbante, C., Morlighem, M., Petersen, T. and Vascon, S., 2025. Machine-learned global glacier ice volumes. arXiv preprint arXiv:2512.11685, link.

- Morlighem, M., Charrassin, R., Maffezzoli, N., Millan, R., Ockenden, H., Schlegel, N-J., Seroussi, H., and Wood, M., 2025. New high-resolution subglacial bed topography and coastal bathymetry of the Antarctic and Greenland Ice Sheets, Philos. Trans. R. Soc. A, in press.

- Maffezzoli, N., Rignot, E., Barbante, C., Petersen, T. and Vascon, S., 2025. A gradient-boosted tree framework to model the ice thickness of the world's glaciers (IceBoost v1. 1). Geoscientific Model Development, 18(9), pp.2545-2568, link.

- Maffezzoli, N., Cook, E., van der Bilt, W.G.M., Støren, E.N., Festi, D., Muthreich, F., Seddon, A.W.R., Burgay, F., Baccolo, G., Mygind, A.R.F. and Petersen, T., 2023. Detection of ice core particles via deep neural networks. Cryosph. 17, 539–565, link.