Claudio Persello
Adjunct Professor
ITC Faculty, University of Twente
Enschede, Netherlands
I have expertise in AI techniques for Earth observation and geospatial applications.
My organisation
About me
Claudio Persello is an Adjunct Professor at the Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente. His main research interests are in the context of machine learning and deep learning for information extraction from remotely sensed images and geospatial data. The activity includes investigating and developing dedicated deep learning techniques for various remote sensing sensor data and multiple applications, focusing on societal and environmental challenges. He is particularly interested in combining deep learning and Earth observation to address and monitor the progress towards sustainable development goals.
Dr Persello is a referee for multiple journals and a program committee member of several conferences in the field of remote sensing and image analysis. He is the Chair of the Image Analysis and Data Fusion (IADF) GRSS technical committee. He is an Associate Editor of the IEEE Transactions on Geoscience and Remote Sensing and a member of the editorial board of the ISPRS Journal of Photogrammetry. He served as publication co-chair for IGARSS 2021. His PhD thesis was awarded the prize for the best PhD thesis on Pattern Recognition published between 2010 and 2012 by the GIRPR, i.e., the Italian branch of the International Association for Pattern Recognition (IAPR). He is a Senior Member of the IEEE.Prof. Claudio Persello has expertise in designing deep learning and GeoAI techniques for extracting geospatial information from Earth observation data. His research group has experience in several GeoAI applications in support of the Sustainable Development Goals. Prof. Persello is the Chair of the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society.
Skills
- Artificial Intelligence
- deep learning
- remote sensing
- Geospatial Information Science
- sustainable development goals
Interests
- GeoAI applications
- Urban applications
- digital twins
- Smallholder farms
- Forest applications
- Glacier mapping and modelling