At OpenGeoHub, Carmelo supports OpenGeoHub's data science projects such as GeoHarmonizer and MOOD H2020. Specific tasks include but are not limited to:
- Installing and maintaining software on local, server and cloud platforms,
- Developing and testing new algorithms and approaches to predictive mapping and machine learning,
- Optimizing computing/minimizing production costs,
- Creating complete data sets, packaged software and software manuals, including tutorials for other researchers,
- Contributing to Open Source Software and Open Data communities through FOSS4G, R, Python and similar communities.
Carmelo has a background in forestry science, with a specialization in forest resources monitoring and management through geospatial data science applications and time series analysis. At OpenGeoHub, Carmelo is a research assistant and PhD candidate (Geo-information Science and Remote Sensing, Wageningen University). He works with designing and conducting research from experimental designs to scientific visualization and communication of science, importing and processing spatial and spatiotemporal data, assisting in training courses and helping in the production of educational materials.
Appointments:
- 2020–present: PhD candidate & research assistant at OpenGeoHub Foundation.