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What belongs here, how entries are chosen, and how to add one.
An AI Scientist is a system that uses foundation models, tools, code, data and sometimes laboratory hardware to carry out or support part of the scientific discovery loop: literature review, hypothesis generation, experiment design, experimentation, analysis and writing. This list collects the strongest work on building and evaluating such systems.
It is deliberately not a general AI-for-Science catalogue. The centre of gravity is agentic scientific work: systems that reason over evidence, call tools, write and execute programs, interact with experiments, and produce artefacts a scientist can inspect and reproduce.
Additions and corrections are welcome. Read the contribution guide, then open an issue or send a pull request.
@misc{awesome_ai_scientist,
title = {Awesome AI Scientist},
year = {2026},
howpublished = {\url{https://github.com/Omni-Scientist/Awesome-AI-Scientist}},
note = {A curated list of AI systems, benchmarks, datasets
and platforms for scientific discovery}
}