Dr Didier Leibovici
Professional Title: Researcher
Other: Researcher in Geocomputational data science & Statistics
Primary domain: Geocomputational Workflow & data Analytics, Spatial data Infrastructure, etc.
Organization name: University of Sheffield
Organization type: Academia/Research
City / Country: Sheffield (UK) - United Kingdom
13 years of research in leading UK universities (Oxford, Leeds, Nottingham); 4 years at IRD (France); international context and European research programme (7 EU projects), UK, France, LMIC (in Africa and South-Asia); 41 articles (19 as 1st author), 55 communications in symposiums (20 extended abstracts, 4-6 pages); Excellent spoken and written French (native) and English (15 years) My research profile in geocomputational data analytics of spatial information with data modelling and statistical analysis, which has developed from my academic experience in both France and the UK dealing with spatio- temporal data from different contexts, such as: spatial epidemiology, agro-ecological monitoring, dynamics of population studies, location based citizen crowdsourcing of environmental information, etc. My approach draws from my dual competency in statistics and computing science, with a focus on providing tools to manage and analyse large datasets from various heterogeneous sources. My research themes are at the intersection of geospatial information science, data mining, computing methodologies and open technologies; I am particularly interested in challenging the potential of interoperability developments. Computing science linked to semantic modelling (e.g. ontologies) or computational architecture (e.g. workflow architectures) supports the data analysis methods I utilise, including multiway methods and spatial statistics of geo-located information for environmental and social studies, which in return can be used in information modelling and retrieval. My focus is on data information interaction, extraction and associations existing in spatio-temporal multi-attribute analysis within integrated modelling approaches. I also consider as essential the meta-information (e.g. provenance, uncertainty and data quality) with conflation and fusion models and its role in the design of the architecture of systems using geocomputational data analytics within an interdisciplinary context. (see full CV http://http://didier.leibovici.free.fr/)