๐ Iโm a Geospatial Data Scientist working at the intersection of Earth Observation, AI, and Big Data, with a passion for enabling sustainable environmental development through open science and digital twin technologies.
๐ข Currently, I work as a Junior Researcher at the Institute for Earth Observation โ Eurac Research, Bolzano, Italy ๐ฎ๐น, where I specialize in climate data downscaling, Earth observation workflows, and high-performance environmental computing.
๐ง My work bridges climate modeling, machine learning, and reproducible research practices. I contribute to international projects like Horizon Europe โ interTwin, support ESA-aligned workflows, and advocate for FAIR data principles in environmental modeling.
๐ I earned my Masterโs degree in Geoinformatics and Spatial Data Science under the supervision of Prof. Edzer Pebesma at the University of Mรผnster, Germany ๐ฉ๐ช, where I focused on reproducible geospatial workflows and open science. During this time, I contributed to the Spatio-Temporal Modelling Lab, extending the open-access book Spatial Data Science with Applications in R by developing Python equivalents for broader accessibility.
๐ฏ Current Focus
- ๐ ๏ธ Scalable EO workflows with STAC + Zarr + openEO
- ๐ก๏ธ Climate downscaling using ML & ESRGAN
- ๐ฌ Digital twin applications for Earth system modeling
- ๐ค FAIR data, reproducibility, and open science
๐ผ I lead or contribute to the development of open-source tools such as:
-
downScaleMLโ high-performance ML downscaling for climate data
(main development happens in the interTwin EU GitLab) -
openeo-processes-daskโ enabling Zarr-native processing and STAC integration
(used in local, scalable EO pipelines) -
raster2stacโ automated STAC metadata generation for EO rasters
(developed within the internal GitLab of Eurac Research)
Most of my core development takes place on GitLab, and this GitHub space serves as a landing page for selected tools, experiments, and community-facing collaborations.
๐งญ Professional Highlights
- ๐ก Developed a two-stage ML downscaling method improving SEAS5 forecast resolution from ~30km to 1km
- ๐ฐ๏ธ Contributed to ESAโs EOPF Zarr service for Sentinel satellite data
- ๐ Built
raster2stac, streamlining metadata generation for FAIR EO data - ๐งช Presented research at EGU, IEEE IGARSS, and won hackathons for EO-based ML solutions
๐ GitHub Stats

