Sajed is a Software Engineer at OpenGeoHub, where he works on high-performance computing (HPC) solutions for large-scale satellite data processing using C++ and Python. His work involves training high-performance machine learning models, including spatiotemporal models, to support large-scale geospatial analysis. He primarily works on backend systems, while also contributing to frontend development when needed.
His responsibilities include:
- Developing and optimizing HPC workflows for satellite data production
- Training and deploying machine learning models for geospatial and time-series data
- Leading global gap-free, cloud-free Landsat program data production.
- Building scalable backend systems for data handling and analysis
- Collaborating across teams to integrate data processing pipelines with user-facing applications
Previously, he worked with SRON Netherlands Institute for Space Research, where he applied computer vision techniques to detect instrument shifts. He also has experience in computer vision tasks such as object tracking and super-resolution modeling. Earlier in his career, Sajed worked in bioinformatics research, publishing several papers before transitioning to remote sensing and satellite data processing. This diverse background allows him to approach complex data challenges from multiple perspectives.