Science and Technology Interest Group
Artificial Intelligence and Machine Learning Science and Technology Interest Group
The NASA Cosmic Origins Program AI/ML Science and Technology Interest Group (AI/ML STIG) addresses the critical need to upskill the astronomy community with AI literacy. We provide structured, domain-specific AI education through stackable, bite-sized modular training designed for astronomical research contexts.
About AI/ML STIG
Building AI Literacy for Astronomical Research
Astrophysics is an emerging technology for big-data science, and the use of Artificial Intelligence (AI) and Machine Learning (ML) technology will be inevitable in the coming decades.
The AI and ML Science and Technology Interest Group (AI/ML STIG) is motivated by the awareness that upskilling the scientific community could have a transformative impact to counter critical challenges facing astronomical research today.
By providing structured, domain-specific AI education, the AI/ML STIG aims to accelerate NASA's competitive advantage in AI-enabled space science, build the interdisciplinary workforce essential for next-generation astronomical discoveries, create a model for other NASA programs facing similar upskilling challenges, and establish NASA’s leadership in responsible AI adoption to maximize the science return from its missions by the community. The modular, community-driven approach ensures scalability while maintaining the rigor and domain relevance essential for meaningful scientific advancement. This STIG serves as a focal point for addressing these challenges through community townhalls for discussions and organizing short tutorials to address specific astronomical AI applications, modules, and foundational concepts.
STIG Leadership
| Yuan-Sen Ting | OSU |
| Alex Gagliano | MIT |
| Siddharth Mishra-Sharma | Boston University |
| Digvijay Wadekar | Johns Hopkins |
| Andrew Saydjari | Princeton |
| Carol Cuesta-Lazaro | MIT |
| Georgios Valogiannis | UChicago |
News & Events
Meetings, conferences, seminars, workshops, and other news and events for the STIG
Convolutional Neural Networks (CNNs) Speaker John Wu, STScI Meeting Connection Join the Meeting
Inductive Biases Speaker John Wu, STScI Lecture notes and slides will be up later on the github repo. We’ll be using slido for Q&A: https://app.sli.do/event/9jLSjC8GYLePQD3RPVXNv5 Meeting Connection Join the Meeting
The next AI/ML Science and Technology Interest Group (AI/ML STIG) lecture will be on 12 January 2026 at 4 pm ET/1 pm PT. The lecture will be given by Dr. John Wu (STScI) on Inductive Biases in Neural Networks. The…
Transformers Speaker Helen Qu, Flatiron Meeting Connection Join the Meeting
Graph Neural Networks (GNNs) Speaker Tri Nguyen, Northwestern Meeting Connection Join the Meeting
Recurrent Neural Networks (RNNs) Speaker Daniel Muthukrishna, Harvard/MIT Meeting Connection Join the Meeting
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