Summary
Didier G. Leibovici is a consultant in data science specialising in geo-spatio-temporal data with over a decade of experience bridging academic research and applied geospatial analytics. He designs interoperable geospatial workflows, spatio-temporal data mining and uncertainty-aware conflation/fusion methods, often implemented in R for environmental, epidemiological and citizen-science applications. His career spans research fellowships across UK institutions and leadership of GeotRYcs, with notable work on climate-sensitive infectious disease modelling and VGI quality assessment in EU-funded projects. Didier blends statistical machine learning with geocomputational modelling and web-service based geo e-infrastructures to support decision-making under data quality constraints. He is motivated by meta-information, error propagation and interdisciplinary collaboration, and maintains active academic ties while running consulting work from Montpellier. An oft-overlooked strength is his sustained focus on practical interoperability—making complex spatio-temporal models reproducible and integrable across platforms.
10 years of coding experience
13 years of employment as a software developer
French, English