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๐Ÿ‘‹ Hello, I'm Suriyah Dhinakaran

๐Ÿš€ Iโ€™m 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.

๐Ÿข Currently, I work as a Junior Researcher at the Institute for Earth Observation โ€“ Eurac Research, Bolzano, Italy ๐Ÿ‡ฎ๐Ÿ‡น, where I specialize in climate data downscaling, Earth observation workflows, and high-performance environmental computing.

๐Ÿง  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.

๐ŸŽ“ I earned my Masterโ€™s degree in Geoinformatics and Spatial Data Science under the supervision of Prof. Edzer Pebesma at the University of Mรผnster, Germany ๐Ÿ‡ฉ๐Ÿ‡ช, 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.


๐ŸŽฏ Current Focus

  • ๐Ÿ› ๏ธ Scalable EO workflows with STAC + Zarr + openEO
  • ๐ŸŒก๏ธ Climate downscaling using ML & ESRGAN
  • ๐Ÿ”ฌ Digital twin applications for Earth system modeling
  • ๐Ÿค FAIR data, reproducibility, and open science

๐Ÿ’ผ 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.


๐Ÿงญ Professional Highlights

  • ๐Ÿ’ก Developed a two-stage ML downscaling method improving SEAS5 forecast resolution from ~30km to 1km
  • ๐Ÿ›ฐ๏ธ Contributed to ESAโ€™s EOPF Zarr service for Sentinel satellite data
  • ๐Ÿ”„ Built raster2stac, streamlining metadata generation for FAIR EO data
  • ๐Ÿงช Presented research at EGU, IEEE IGARSS, and won hackathons for EO-based ML solutions

๐Ÿ“ซ Get in touch
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๐Ÿ“Š GitHub Stats

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