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.
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.
Established under the Cosmic Origins Program Analysis Group (COPAG), the STIG brings together researchers and educators to build a comprehensive AI education framework tailored for the astronomy community.
All lecture materials are open-source and designed to serve as templates for speakers and educators in the astronomy community.
The Future of AI and the Mathematical and Physical Sciences
Jesse Thaler, MIT
An overview of how AI is transforming the mathematical and physical sciences, exploring opportunities and strategic priorities for the astronomy and astrophysics community. Based on the NSF Future of AI+MPS Workshop white paper.
Topics Covered:
Large Language Models as Research Agents: Part 1
Yuan-Sen Ting, The Ohio State University
Learn the fundamentals of working with LLM APIs—making calls, managing conversations, and crafting effective prompts. Master key parameters, build multi-turn conversations, and implement prompting strategies for research tasks.
Topics Covered:
Large Language Models as Research Agents: Part 2
Yuan-Sen Ting, The Ohio State University
Break through LLM limitations with function tools and Retrieval Augmented Generation. Build astronomical calculation tools, implement document-based Q&A, and create powerful research assistants.
Topics Covered:
Duration: 26-week series (November 1, 2025 - May 31, 2026)
Format: Weekly 1-hour sessions (40-45 mins + questions)
Time: Mondays at 4:00 PM ET
Delivery: Remote only
Zoom Link: Join Meeting
| Week | Date | Topic | Speaker |
|---|---|---|---|
| 1 | Nov 3 | Overview | Jesse Thaler, MIT |
| Module 1: Large Language Models as Autonomous Agents | |||
| 2 | Nov 10 | LLM API Basics | Yuan-Sen Ting, OSU |
| 3 | Nov 17 | RAG & Function Tools | Yuan-Sen Ting, OSU |
| 4 | Nov 24 | LLM as Agent | Francisco Villaescusa-Navarro, Flatiron |
| Module 2: Computing Resources | |||
| 5 | Dec 1 | NASA/NSF Programs (ACCESS, NAIRR) | TBD |
| Module 3: Deep Learning Frameworks | |||
| 6-7 | Dec 8 & 15 | PyTorch/JAX | TBD |
| Module 4: Neural Network Theory | |||
| 8 | Jan 5 | Inductive Biases | John Wu, STScI |
| Module 5: Neural Network Architectures | |||
| 9 | Jan 12 | Convolutional Neural Networks (CNNs) | John Wu, STScI |
| 10 | Jan 19 | Recurrent Neural Networks (RNNs) | TBD |
| 11 | Jan 26 | Graph Neural Networks (GNNs) | TBD |
| 12 | Feb 2 | Transformers | TBD |
| Module 6: Physics-Inspired Networks | |||
| 13 | Feb 9 | Equivariant Networks - Theory | TBD |
| 14 | Feb 16 | Equivariant Networks - Applications | TBD |
| Town Halls | |||
| 15 | Feb 23 | Mid-Series Town Hall | — |
| Module 7: Generative Models | |||
| 16-20 | Mar 2 - Mar 30 | Normalizing Flows, Diffusion Models, Flow Matching, Simulation-Based Inference | TBD |
| Module 8: Reinforcement Learning | |||
| 21-23 | Apr 6 - Apr 20 | RL Fundamentals, Applications to Instrumentation & Telescope Scheduling | TBD |
| Module 9: Data & Future | |||
| 24 | Apr 27 | Open-Source Datasets and Best Practices | TBD |
| 25 | May 4 | Foundation Models for Astronomy | TBD |
| Town Halls | |||
| 26 | May 11 | Final Town Hall | — |
For inquiries, please contact: ting.74@osu.edu
The AI/ML STIG is open to the national and international community without regard to institutional affiliation, education, or career status. We welcome astronomers, astrophysicists, data scientists, and anyone interested in AI applications in astronomy.
Mailing List: Stay updated on upcoming lectures, events, and resources
Please send an email to AI-ML-STIG-join@lists.nasa.gov with the subject line "Join" to be added to the AI/ML STIG email list.
All lecture recordings will be hosted on the NASA Cosmic Origins Program subpage, making them accessible to the broader community for asynchronous learning.