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:
-
downScaleML
โ high-performance ML downscaling for climate data
(main development happens in the interTwin EU GitLab) -
openeo-processes-dask
โ enabling Zarr-native processing and STAC integration
(used in local, scalable EO pipelines) -
raster2stac
โ 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