The Sched app allows you to build your schedule but is not a substitute for your event registration. You must be registered for PyTorch Conference Europe 2026 to participate in the sessions. If you have not registered but would like to join us, please go to the event registration page to purchase a registration.
This schedule is automatically displayed in CEST (UTC/GMT +2). To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date."
Sign up or log in to add sessions to your schedule and sync them to your phone or calendar.
With the advent of geospatial foundation models, unexplored use cases are emerging that require well-curated datasets. Currently, no standardised approach exists for creating such AI-ready geospatial datasets. In this session, we introduce TerraKit: a comprehensive open-source Python library for retrieving, and processing geospatial data, that seamlessly integrates with upstream geospatial model training libraries such as TorchGeo or TerraTorch.
From raster/vector annotations, TerraKit will match, download, process, align and split the requested data source (e.g., EarthData, CDSE, Planetary Computer) based on user specifications provided by a simple configuration file. TerraKit also supports spatial train/val splits and exports datasets in standard formats such as TACO datasets. TerraKit streamlines the pipeline from raw EO data to AI-ready datasets, accelerating the development of custom geospatial applications, and ensuring query and processing pipelines are reproducible. By lowering the barrier to entry, a wider community of TorchGeo and TerraTorch users are empowered to leverage foundation models for Earth observation.
Rosie is a Research Software Engineer at IBM, specializing in the
development of next-generation tools and technologies designed to
drastically accelerate solutions for today’s most urgent global
challenges. Her technical focus involves leveraging geospatial data, AI
models... Read More →
