2014-present Guest Professor/Senior Researcher, Department of Electronics and Informatics, Vrije Universiteit Brussel

2013-2014 Marie Curie Fellow, Fondazione Edmund Mach (TN, Italy)

2011-2012 Senior Researcher, Department of Electronics and Informatics, Vrije Universiteit Brussel

2005-2011 Doctor Assistant, Geography Department, Vrije Universiteit Brussel

2001-2005 Post-doc Engineer, Interuniversity MicroElectronics Centre (IMEC), Leuven, Belgium
1998-2001 Research Scientist, University of Maryland, College Park, USA

Jonathan Cheung-Wai Chan is an expert in remote sensing with a special focus on machine learning algorithms for land cover mapping using hyperspectral data. His recent research activities focus on enhancement of Earth Observation hyperspectral remote sensing data, e.g. spatial and spectral superresolution using Deep Learning and Sparse Theory.

Shortly after obtaining his PhD from the University of Hong Kong (1999), he worked as a research scientist at the Geography Department, at University of Maryland, College Park, the United States. He was involved in various NASA projects in relation to global mapping using machine learning algorithms (C5.0, Bagging, Boosting). In 2001, he was hired as a post-doc researcher at InterUniversity MicroElectronics Research Center (IMEC) at Leuven, stationed at the Department of Electronics and Informatics (ETRO), at Vrije Universiteit Brussel (VUB). He worked on European projects using remote sensing methods for humanitarian demining (Thermal Infrared sensor, UAV HD multi-spectral analysis). From 2005 to 2011, he was a Doctor Assistant at the Geography Department at VUB where he led research projects for exploitation of airborne and spaceborne hyperspectral remote sensing with machine learning algorithms in detailed land use/land cover mapping (NATURA 2000 ecotope mapping for biodiversity) and impervious surface estimation for hydrological modeling in urban area.

From 2013-2015, he was a Marie Curie Fellow under the stream of Marie Curie Industry-Academia Partnerships and Pathways (IAPP) program, at Fondazione Edmund Mach, Trentino, Italy. Research in Hyperspectral/Lidar Fusion of for forestry inventory.

He serves regularly in the Technical and Scientific Committees of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) and has chaired several special sessions in IGARSS on Spatial Superresolution and Subpixel Classifications of hyperspectral data.

He belongs to the editorial board of the journal Remote Sensing. He is the Guest Editor of two Special Issues: Deep Learning and Data Mining for Hyperspectral Imagery, Special Issue, Remote Sensing (2019). Spatial Enhancement of Hyperspectral Data and Applications, Special Issue, Remote Sensing (2017).

He is the coordinator of E.C. Erasmus + Capacity Building projects (1) UN4DRR #University Network for Disaster Risk Reduction and Management in Indian Ocean Rim (2019-2022) and (2) NEXUS #Nodes of EXcellence in (SEA) Universities through Spatial data (2017-2020) https://sea-spatialdata-nexus.com