Advance your academic career, collaborate globally, and expand your network— join now !

Didier G Leibovici

Dr. Didier G Leibovici

School of Mathematics & Statistics, University of Sheffield, UK

Share Link

Share

Information

Didier Leibovici’s expertise is in geospatial data analytics, and after 15 years of research in leading UK universities (Oxford, Leeds, Nottingham, and Sheffield); 5 years at IRD (France); 2 years at Sanofi-Recherche (France); and 4 years at INSERM (France) working within interdisciplinary and international context for European research programmes with the UK, France, LMIC (in Africa and South-Asia), he is setting up GeotRYcs, a geo-spatial-temporal data scientist consulting service. Didier has a PhD in biostatistics and a Master’s degree in computing science; his scientific research in data analysis and geospatial science including data interoperability and uncertainty are focused on spatiotemporal data modelling and analysis within different contexts, such as epidemiology, agriculture and agro-ecological monitoring, dynamics in population studies, and location-based citizen crowdsourcing of environmental information within interdisciplinary projects.

Research Keywords & Expertise

Spatial Analysis
Clustering
Statistical Machine Le...
Spatial Data Quality
Geo-computational data...

Fingerprints

17%
Clustering
5%
Spatial Analysis
5%
Spatial Data Quality
5%
Scientific workflow modelling

Short Biography

Didier Leibovici’s expertise is in geospatial data analytics, and after 15 years of research in leading UK universities (Oxford, Leeds, Nottingham, and Sheffield); 5 years at IRD (France); 2 years at Sanofi-Recherche (France); and 4 years at INSERM (France) working within interdisciplinary and international context for European research programmes with the UK, France, LMIC (in Africa and South-Asia), he is setting up GeotRYcs, a geo-spatial-temporal data scientist consulting service. Didier has a PhD in biostatistics and a Master’s degree in computing science; his scientific research in data analysis and geospatial science including data interoperability and uncertainty are focused on spatiotemporal data modelling and analysis within different contexts, such as epidemiology, agriculture and agro-ecological monitoring, dynamics in population studies, and location-based citizen crowdsourcing of environmental information within interdisciplinary projects.