I am a geospatial engineer working in the field of remote sensing, machine learning and cloud computing and related open source projects. I have a background in Computer Vision and worked in this field before.
The image presented above is a view from space of the city of Bolzano (Italy), which combines data from two Copernicus missions: Sentinel-1 and Sentinel-2. It has been generated by me for the EuroGeo Wokshop 2023 using tools and software I am contributing to develop:
- openEO:
- Maintainer of the openEO API back-end infrastructure of Eurac Research available at openeo.eurac.edu
- Contributor to several related open-source projects:
- openeo-processes-dask : Xarray and Dask implementation of the openEO processes
- openeo-pg-parser-networkx : (JSON) openEO process graph parser
- openeo-spring-driver : openEO API implementation in Java (Spring)
- openeo-python-client : openEO Python client. Implemented the Client Side Processing functionality.
- openeo-test-suite : automated testing suite for openEO back-ends
- openeo_odc_driver : containerized (Docker) openEO processing engine
- openEO_photovoltaic : mapping photovoltaic panels in the cloud
- SAR2Cube: Sentinel-1 SLC InSAR processing in the cloud, on-the-fly generation of interferometric coherence and more.
- STAC:
- Main developer of the raster2stac Python package, which allows the creation of STAC Collection with Items and Assets starting from different kinds of raster datasets. The goal is to make a dataset easily accessible, interoperable, and shareable.
📹 Computer Vision / Deep Learning
- ViDeNN: Deep Blind Video Denoising : tensorflow model to denoise videos affected by different types of degradation, such as Additive White Gaussian Noise and videos in Low-Light conditions.
- DnCNN: Beyond a Gaussian Denoiser : Residual Learning of Deep CNN for Image Denoising. Extended model to RGB with this PR.