Claudio Persello

M-GEO
M-SE
Humanitarian Engineering
GEM
ACQUAL

Explainable AI and Foundational Models for large-area crop type and yield mapping in data-scarce environments

In many parts of the world, agricultural monitoring is hindered by limited field data, inconsistent surveys, and highly heterogeneous landscapes.

M-GEO
M-SE
ACQUAL

Deep learning for integration of Satellite images and google StreetView for mapping informal settlements (slums)

Mapping and monitoring slums is essential to ensure the sustainable development of the cities to ensure a quality of life for people.

M-GEO
M-SE
ACQUAL

Deep Learning based multisource data fusion for detecting deforestation (Supervision in collaboration with INPE/Brazil)

An accurate method for automatically mapping deforested areas constitute an important tool to inform and enable deforestation containment policies.

GIMA
M-GEO
M-SE
ACQUAL
PLUS

Modelling urban socio-economic inequalities - living conditions - deprivation (slums) using machine learning and earth observation (topic has several sub-topics)

LINK TO RESEARCH PROJECTS

The MSc topics link to several ongoing larger research projects that allow being part of international research teams - both projects just started:

M-GEO
M-SE
GEM
GIMA
4D-EARTH
ACQUAL
PLUS

Digital Twins for sustainable cities and environments

Digital Twins (DTs) are rapidly becoming one of the most exciting innovations in smart cities, bringing together 3D modelling, geospatial data, IoT sensors, and AI t

M-GEO
M-SE
GIMA
ACQUAL
PLUS

AI-Powered Digital Twins for the Cities of Tomorrow

Generative AI and Digital Twins (DTs) are redefining how urban environments are conceptualized, designed, and managed.

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