About
High-profile voices in AI research and industry have forecasted that AGI will “cure all diseases” and that due to developments in AI, “scientific progress will likely be much faster than it is today”. While these statements underscore the rapid and exciting developments in the AI for Science community, beneath the headlines lie unresolved questions about where current AI methods genuinely advance scientific discovery and where they still hit hard limits. Through our proposed AI for Science workshop, we will bring together experimentalists, domain scientists, and ML researchers to discuss where this boundary lies. Our workshop will highlight common bottlenecks in developing AI methods across scientific application domains, and delve into solutions that can unlock progress across all of these domains. We welcome submissions from all AI for Science areas, but we concentrate our talks and panel on the reach and limits of AI for scientific discovery. The main objectives include:
- Multi-domain scientific reasoning
- Benchmark how well today’s LLMs and autonomous agents generate rigorously testable hypotheses and interpret results that span physics, chemistry, biology, climate science, and beyond.
- Identify failure modes in cross-disciplinary reasoning and outline directions–e.g., tool-augmented prompting, graph-structured memory, retrieval pipelines—-to close these gaps.
- High-fidelity generative & surrogate simulators
- Survey state-of-the-art models—from all-atom biomolecular generators to neural weather simulators—and assess the spatial, temporal, and accuracy limits they still cannot cross.
- Convene domain and ML experts to design hybrid, physics-informed, or multiscale approaches that push simulation fidelity where classical or purely data-driven methods plateau.
- Experimental data scarcity & bias
- Spotlight scientific areas that lack “Protein-Data-Bank–level” resources and invite dataset-generation proposals to catalyze community efforts.
- Explore lab-in-the-loop strategies—active learning, autonomous experimentation, synthetic data augmentation—to overcome limited or biased measurements and accelerate model improvement.
New AI for Science White Paper Competition
We introduce a white paper competition, to encourage researchers to identify shared resources that have the potential to accelerate the pace of scientific research. These shared resources include large, diverse, high-quality datasets, benchmarks for evaluating the performance of AI algorithms, the integration of AI and simulation software, software that enables inverse design, and self-driving labs. The goal of the competition is to catalyze follow-on investment from government and philanthropy for at least one of the ideas, within 3-6 months one year of the announcement of the winning ideas. We secure a total of $25K fund, where $15K will be used for prizes and $10K will be used for honoraria for volunteers (judging, marketing). We will post the details later.
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Invited Talks (In alphabetical order)
Panel: From Atoms to Answers: Can AI Simulate Science and Explain It?
Important Dates (Anywhere on Earth)
- Abstract Submission Deadline: Aug 18, 2025
- Paper Submission Deadline: Aug 25, 2025
- Review Bidding Period: Aug 25-27, 2025
- Review Deadline: Sep 18, 2025
- Acceptance Notification Date: Sep 22, 2025
- Workshop Date: Dec 6-7, 2025
Submissions
Please submit your paper in Openreview. Our workshop is nonarchival, the accepted papers will be posted on our website.
Frequent Q&A
- What is the abstract deadline and why do we have it?
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You only need to create a submission tab on OpenReview by the abstract deadline. (This is not a separate submission track for short papers). As we receive a large volume of diverse submissions, to entire good review quality and coverage of reviewer areas, we keep an abstract deadline for us to have a chance to invite new reviewers if needed.
- Can I attend the workshop even if I don’t have any submissions?
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Yes, you are welcome to attend the workshop. Registration is through NeurIPS 2025 registration system with workshop selected.
- Can I join the organizing team?
- We always welcome new members to join our organizing team, feel free to reach out to us if you are interested. Several questions are recommended to be answered to help us make decision: what do you like about the workshop? what do you think we should improve? what can you contribute to the organizing team?
Organizers and Contact
For any question, please contact ai4sciencecommunity@gmail.com.
Organizers
