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AI/ML STIG Lecture Series

Artificial Intelligence and Machine Learning Science and Technology Interest Group (AI/ML STIG)

AI/ML STIG about AI/ML STIG Lecture Series

Location

Virtual

Dates

2 February 2026
4:00pm ET

Community

AI/ML STIG

Type

Seminar

Graph Neural Networks (GNNs)

Speaker

Tri Nguyen, Northwestern

Learn how to build Graph Neural Networks (GNNs) to work with graph-structured data. Explore node classification on citation networks and apply GNNs to model dark matter subhalo interactions with stellar streams using real astrophysical simulations. Lecture tutorial materials and jupyter notebooks can be found here: https://tingyuansen.github.io/NASA_AI_ML_STIG/#schedule

Topics Covered:

  • Introduction to graph-structured data and GNNs
  • Node classification with the Cora citation network
  • Building GNNs with PyTorch Geometric
  • Graph attention mechanisms and message passing
  • Application: inferring dark matter subhalo properties from stellar streams
  • Working with point cloud data in astronomy
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Angled from the upper left corner to the lower right corner is a cone-shaped orange-red cloud known as Herbig-Haro 49/50. This feature takes up about three-fourths of the length of this angle. The upper left end of this feature has a translucent, rounded end. The conical feature widens slightly from the rounded end at the upper right down to the lower right. Along the cone there are additional rounded edges, like edges of a wave, and intricate foamy-like details, as well as a clearer view of the black background of space. In the upper left, overlapping with the rounded end of Herbig-Haro 49/50, is a background spiral galaxy with a concentrated blue center that fades outward to blend with red spiral arms. The background of space is speckled with some white stars and smaller, more numerous, fainter white galaxies throughout.