Nicolo Grometto
Image:
Petter Bjørklund / SFI Visual Intelligence

Nicolo Grometto

Meet Nicolo, our newest Doctoral Research Fellow

We happily welcome Nicolo Grometto as a new PhD Candidate at SFI Visual Intelligence in Bodø, Norway.

Meet Nicolo, our newest Doctoral Research Fellow

We happily welcome Nicolo Grometto as a new PhD Candidate at SFI Visual Intelligence in Bodø, Norway.

By: Petter Bjørklund, Communication Officer at SFI Visual Intelligence

Grometto is originally from Italy and recently joined the Department of Computer Science at UiT in Bodø to work on his PhD project in collaboration with industry partner Kongsberg Satellite Services (KSAT).

He completed his graduate-level education in Statistics and Operations Research at ETH Zurich and Princeton University. Before joining UiT, his previous research focused on probabilistic methods in combinatorics and random matrix theory. He also worked as a mathematics teacher in an international high school in South-West Norway

His PhD project focuses on uncertainty quantification in deep learning for Earth observation. Building on theoretical foundations in Bayesian deep learning, Grometto's research seeks to develop methods that not only improve overall predictive accuracy but also provide reliable uncertainty estimates for critical environmental monitoring tasks.

"My work aims to address challenges in remote sensing applications where labeled data is scarce and model reliability is paramount. Examples include advancing segmentation techniques for marine habitat mapping and developing robust detection systems for marine pollution events, such as oil spills," Grometto explains.

Coming from a theoretical background in statisics, Grometto says he is particularly interested in gaining additional exposure to applied research.

"I am very excited to work at the intersection of theory and applied research to tackle complex environmental problems. The opportunity to collaborate within an international and interdisciplinary team brings diverse perspectives that are essential for tackling these challenges," Grometto says.

"I am looking forward to learning how to effectively leverage a range of different modalities for my research, ranging from hyperspectral images to synthetic aperture radar data," he concludes.

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