The workshop aims to bring together researchers with hands-on experience in using advanced Large Language Models (LLMs), such as ChatGPT and Claude, to explore their potential applications in astrophysical research, share expertise, and collaboratively develop practical tools and workflows.
The workshop will focus on two main objectives:
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Productivity: How can state-of-the-art LLMs improve the efficiency and effectiveness of astrophysical research? Which tools and approaches are most useful, how can they be integrated into existing research workflows, and how can best practices be shared across the community?
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Scientific validation: How can AI-assisted research meet the standards of scientific rigour, reproducibility, and publication? Which validation strategies are effective, and what are the capabilities and limitations of these tools?
Workshop format
To encourage active participation and productive exchanges, attendance is limited to 20 selected participants. Priority will be given to individuals with prior practical experience who are eager to share their insights. This information will be gathered through the expression of interest form, so applicants are highly encouraged to highlight their practical background. Please note that this workshop will be an in-person-only event.
The programme will combine a small number of introductory and invited talks with interactive round-table discussions and hands-on hackathon sessions. Particular emphasis will be placed on collaborative work, with the goal of developing concrete tools, identifying best practices, and exploring solutions to challenges relevant to the astrophysical community.
Practical information
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Dates: 26–28 January 2027 (9:30 - 17:30)
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Venue: Room 214 CNR Area (Bologna, Italy)
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There will be no registration fee (meals will not be provided)
Further details regarding the programme and participation will be communicated in due course. We look forward to bringing together researchers interested in shaping the effective, reliable, and scientifically rigorous use of state-of-the-art AI in astrophysics.
Confirmed Invited:
- James Nightingale (University of Newcastle)