Research Papers
7–9 pages in NeurIPS format; page limits exclude references; appendices have no length limit but are not considered in scoring.
Machine Learning/CORE Unranked
AI4ChipDesign 2026
AI for Chip Design - NeurIPS 2026 Workshop
AI for Chip Design 2026 is a NeurIPS workshop bringing together researchers from machine learning and electronic design automation (EDA) to advance AI-driven approaches in semiconductor design. The workshop focuses on novel applications of AI for chip design automation, including physical design, verification, synthesis, and hardware-aware learning, with an emphasis on reproducibility and community collaboration.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Poster Papers
3–4 pages in NeurIPS format; may include position papers, exploratory work, highly experimental research, or applied research contributions.
Research areas in scope
01
Topics of Interest
Machine learning for physical design: placement, routing, and floorplanningML for RTL, logic synthesis, and technology mappingTiming, power, and area prediction and optimizationGraph neural networks for circuits and netlistsGenerative models (e.g., diffusion, flow matching) for layout and designReinforcement learning for EDA tasks, including script generation, testbench production, and module completionLarge language models and foundation models for hardware description languages (Verilog, VHDL, and SystemVerilog)Agentic systems for chip design workflows with tool use (linters, synthesizers, simulators, timing analyzers, etc.)Reproducible benchmarks, datasets, and open-source infrastructureSocietal, educational, and workforce aspects of AI-driven chip design
Policies worth checking twice
- All submissions will receive at least three double-blind reviews.
- Submissions must use the official NeurIPS 2026 style files and formatting guidelines.
- Page limits exclude references; appendices have no length limit but reviewers are encouraged not to consider them for scoring.
- This workshop is non-archival: accepted papers will not appear in NeurIPS proceedings but will be publicly posted on OpenReview.
- All papers and posters must be presented in person; works without an in-person presenter will be removed.
- Authors may use LLMs in accordance with NeurIPS 2026 policy, but remain fully responsible for correctness, originality, and integrity of submissions.
- Reviewers must not use LLMs or other generative AI systems to review submissions or upload confidential manuscripts to external AI services.
- This workshop does not adopt the optional AI-assisted reviewing experiment from the NeurIPS 2026 main conference.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026