AI for Sciences Track (First Edition): Call for Papers
KDD is the premier Data Science and AI conference, traditionally hosting a Research and an Applied Data Science Track (and recently a newly introduced Datasets & Benchmarks Track). The conference of 2026 will take place from August 9 to 13, 2026, in Jeju, Korea.
This year, we are introducing another new track of AI for Sciences, highlighting the increasingly important roles of AI and data-driven methods for interdisciplinary research and scientific discoveries.
KDD has two submission cycles per year. Submissions to the new AI for Sciences Track are only accepted in the Second Cycle (February 2026). Papers submitted to all other tracks during this Second Cycle are not eligible for consideration in the AI for Sciences Track. Papers rejected from other tracks in the First Cycle can be submitted only if the topics are highly related to the AI for Sciences Track.
The important dates for the KDD 2026 Second Cycle are:
- Abstract Deadline: Feb 1, 2026
- Paper Deadline: Feb 8, 2026
- Author Rebuttal Period: Apr 4-18, 2026
- Notification: May 16, 2026
- Camera-ready: TBD
All deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.
Submission Site
We are using OpenReview to manage the submissions and reviewing. Submissions will not be made public on OpenReview during the reviewing period.
All listed authors must have an up-to-date OpenReview profile. Here is information on how to create an OpenReview profile. Note OpenReview’s moderation policy for newly created profiles:
- New profiles created without an institutional email will go through a moderation process that can take up to two weeks.
- New profiles created with an institutional email will be activated automatically.
The OpenReview profile will be used to handle conflict of interest and paper matching. An incomplete OpenReview profile is sufficient ground for desk rejection.
To be considered complete, each author profile must be properly attributed with the following mandatory fields: current and past institutional affiliation (going back at least 5 years), homepage, DBLP (if there is prior publication), ORCID, Advisors and Recent Publications (if any). In addition, other fields such as Google Scholar, LinkedIn, Semantic Scholar, Advisees and Other Relations should be entered wherever applicable.
Abstracts and papers can be submitted through OpenReview at this link: KDD 2026 AI4Sciences Track February | OpenReview
Scope
The AI for Sciences Track aims to bring together researchers from AI, data sciences, and domain disciplines to advance the next generation of data-driven interdisciplinary research and scientific discovery. We focus on methods that enable interpretable and trustworthy AI systems to accelerate progress in various disciplines of science. The topics covered by this track include and are not limited to:
- AI-driven Scientific Discovery: Using machine learning and generative models to propose hypotheses and identify new laws or relationships in data.
- AI-accelerated Simulations and Modeling: Integrating neural surrogates, physics-informed models, or reinforcement learning to speed up scientific simulations and numerical solvers.
- AI for Data-rich Science: Handling massive experimental, observational, or sensor data (e.g., in genomics, particle physics, astronomy, climate science).
- Scientific Foundation Models: Developing large-scale, cross-domain models that capture fundamental structures across scientific data (e.g., molecule-language models, multimodal science models).
The interdisciplinary scientific domains include and are not limited to
- Physical Sciences: Quantum chemistry, materials science, condensed matter physics, high-energy physics, astrophysics.
- Biomedical Sciences: Health sciences, healthcare, bioinformatics, epidemiology, pharmaceuticals.
- Life Sciences: Systems biology, multiomics, neuroscience, plant/animal biology.
- Environmental and Earth Sciences: Ecology, climate, agriculture, hydrology, energy systems, sustainability analytics.
- Robotics and Automation: AI-driven design and control, robotics for scientific experiments.
- Transportation and Urban Systems: Modeling human behavior and mobility patterns, predicting human and vehicle trajectories, and developing planning and optimization methods under resource constraints for AI-powered smart cities.
- Social Sciences and Economics: Modeling human systems, policy simulations, and complex adaptive systems.
Evaluation Criteria
Submissions will be reviewed with the same rigor as the main KDD conference but tailored to the specific needs and challenges of AI for Sciences. The key evaluation criteria include:
- Unique Data & Analysis: We encourage the use of domain-specific data that drive novel methodology designs and scientific discoveries. The datasets are encouraged but not required to be made publicly available before or after the publication. However, clear, detailed descriptions of how data was collected, preprocessed, managed, and analyzed are required.
- Focus of Studies: The studies should focus on advancing the science within the targeted discipline(s), with innovative use of AI, outline the challenges and gaps in adapting advanced AI methodologies innovatively to the specific scientific problems and associated datasets, highlight the scientific discoveries if any, with rigorous and comprehensive analysis and validations, and include only necessary theoretical and methodological contributions (i.e., avoid re-inventing the wheels solely for the purpose of technical innovations).
- Interdisciplinary Collaborations: We encourage collaborations between disciplines, especially across AI/ML and the targeted scientific domains. Specifically, we expect submissions co-authored by experts from domains relevant to the studies, with clear domain-specific affiliations. Authors from the targeted domains are also expected to clearly underscore the key contributions of the work to their domain, along with discussions on specific challenges tackled by AI/ML as well as the challenges with using AI/ML in their domain of expertise.
- Ethics, Fairness, and Limitations: Submissions are required to address ethical considerations, including data privacy, consent, bias, and potential misuse as well as the limitations of the presented work. Authors are required to include a separate section titled Limitations and Ethical Considerations in the paper.
Submission Guidelines
Deadlines. The submission deadlines are strict and no extensions, regardless of circumstances, will be allowed. Placeholder or dummy abstracts are forbidden.
Authorship. The ACM has an authorship policy stating who can be considered an author in a submission as well as the use of generative AI tools. Every person named as the author of a paper must have contributed substantially to the work described in the paper and/or to the writing of the paper and must take responsibility for the entire content of a paper. Any use of generative AI tools must be disclosed and elaborated in the submission form.
Authorship changes. The full list of author names, including the ordering, must be finalized by the submission deadline. There cannot be any addition, removal, or reordering of authors after the submission deadline. The only changes allowed are the correction of spelling mistakes or new affiliation.
Anonymity. The review process for the AI for Sciences Track will be single-blind. Author names and affiliations should be listed.
Types of Submissions. The AI for Sciences Track is calling for three types of papers: 8-page full papers (focusing on complete research), 4-page short papers (focusing on on-going research and/or preliminary results), and 2-page extended abstracts (focusing on published high-quality research). All full and short papers should present original unpublished work (refer to the Originality and Concurrent Submissions section), whereas all extended abstracts should describe work already published or accepted at high-impact journals– with a separate section titled Original Publication and Relevance to KDD in the paper clarifying the original publication venue and why the work is relevant to KDD. All full papers will be published by ACM and accessible via the ACM Digital Library upon acceptance. All short papers and extended abstracts will have an option of being published and included in the conference proceedings or not.
Formatting Requirements. Submissions must be in English, in double-column format, and must adhere to the ACM template and format (also available in Overleaf); Word users may use the Word Interim Template. The recommended setting for LaTeX is:
\documentclass[sigconf,review]{acmart}
Submissions must be a single PDF file: 8/4/2 content pages as main paper, followed by References and an optional Appendix that has no page limits. All regular and required sections should be included in the main paper. The Appendix can only contain details on reproducibility, proofs, pseudo-code, etc. The first 8/4/2 pages should be self-contained, since reviewers are not required to read past that. Note that different limits will apply to camera-ready (refer to the Publication section).
Originality and Concurrent Submissions. All full and short papers must present original work—this means that papers under review at or published/accepted to any peer-reviewed conference/journal with published proceedings cannot be submitted. Submissions that have been previously presented orally, as posters or abstracts-only, or in non-archival venues with no formal proceedings, including workshops or PhD symposia without proceedings, are allowed. Authors may submit anonymized work that is already available as a preprint (e.g., on arXiv or SSRN) without citing it. The ACM has a strict policy against plagiarism, misrepresentation, and falsification that applies to all publications.
Resubmission. There will be no “Resubmit” decisions in this track. All papers will be a fresh submission during each cycle.
Serving as Reviewer. To ensure that all papers receive a sufficient number of high-quality reviews, there is a requirement for authors to contribute to reviewing.
- Every submission must nominate at least one author who is a qualified reviewer (i.e., authors with at least three papers in top AI/ML conferences or journals such as KDD, NeurIPS, ICML, and JMLR, or at least one paper in top scientific journals such as the main or sub-journals of Nature, Science, and Cell). Only if no qualified reviewer exists in the author list, the submission should nominate the best-qualified author(s) for consideration by the PC chairs.
- Any author listed on two or more papers may be automatically signed up as a reviewer unless they are already serving as a reviewer, AC, or SAC.
Either case above constitutes an acceptance and a commitment to carry out the regular reviewing load responsibly. Failure to provide a qualified reviewer when one exists in the author list, or failure to carry out the assigned reviewing duty properly, is grounds for desk rejection.
Ethical Use of Data and Informed Consent. Authors are required to include a separate section titled Limitations and Ethical Considerations in the paper to address the ethical use of data and/or informed consent of research subjects. You and your co-authors are subject to all ACM Publications Policies, including ACM’s Publications Policy on Research Involving Human Participants and Subjects (posted in 2021). Please ensure all authors are familiar with these policies.
Please consult the regulations of your institution(s) indicating when a review by an Institutional Ethics Review Board (IRB) is needed. Note that submitting your research for approval by such may not always be sufficient. Even if such research has been approved by your IRB, the program committee might raise additional concerns about the ethical implications of the work and include these concerns in its review.
Submissions that do not follow these guidelines or do not view or print properly, will be desk-rejected.
Reviewing Process
Reviewing. Each submission will receive at least three independent reviews, overseen by an Area Chair (AC). If any author of a submission, who is also a reviewer, does not carry out the reviewing task in a proper and timely manner, no author of that submission will see the reviews of that submission during the rebuttal stage.
Any use of generative AI tools during the reviewing process must be disclosed in the review form. In particular, verbatim uploading of any passage from the paper being reviewed to any generative AI tool is forbidden.
Rebuttal. Authors will have the chance to provide a response to each review during the rebuttal period. The ACs will consider the authors’ response to the points raised by the reviewers, as well as discussion among reviewers, to inform acceptance decisions.
Withdrawal. Authors may use the withdrawal button on OpenReview up until the end of the rebuttal period. Beyond that, any request to withdraw must be made to the PC Chairs in writing, and approval for late withdrawal is at the discretion of PC Chairs. If withdrawal is made after reviews have been revealed to authors, the paper will face a 12-month waiting period before it could be submitted to KDD again.
Decision. A range of factors including technical merit, originality, potential impact, quality of execution, quality of presentation, related work, reproducibility of results, and ethics, will be used by the ACs to make a recommendation. The PC Chairs will make the final decisions.
Transparency. By submitting paper(s) to KDD 2026, the authors agree that the original submission, reviews, meta-reviews, and discussions will be made public in OpenReview for all accepted papers.
Conflict of Interest (COI) Policy
All authors and reviewers must declare conflicts of interest in OpenReview. A domain conflict (entered in Education & Career History) must be declared for employment at the same institution or company, regardless of geography/location, currently or in the last 12 months. A personal conflict should be declared when the following associations exist:
- candidate for employment at the same institution or company
- co-author on book/paper or co-PI on a funded grant/research proposal in the last 24 months
- active collaborator
- family relationship or close personal relationship
- graduate advisee/advisor relationship, regardless of time elapsed since graduation
- deep personal animosity
In general, we expect authors, PC, the organizing committee, and other volunteers to adhere to ACM’s Conflict of Interest Policy as well as the ACM’s Code of Ethics and Professional Conduct.
Any transgression that falls short of ethical standards will be investigated and may face disciplinary actions. Such transgressions include, but are not limited to, falsification, dual submission, collusion, pressuring any member of the program committee. Convicted misconduct may result in a 3-year ban from SIGKDD events for all the authors.
To assess and be able to exclude CFP violations, authors must give consent to the SIGKDD to process and share their submission and other relevant data pertaining to the submission such as authors’ names, affiliations, and email addresses to related conference organizations. Any and all data will be processed by only the respective Program Chairs and the Ethics Committee Members.
Publication and Presentation Policies
Publication. All accepted full papers will be published by ACM and will be accessible via the ACM Digital Library, whereas all accepted short papers and extended abstracts will have an option to be published and included in the conference proceedings or not. In the proceedings, each full paper will be allowed 12 pages (of which 9 pages are content pages), each short paper will be allowed 6 pages (of which 4.5 are content pages), and each extended abstract will be allowed 3 pages (of which 2 are content pages). The additional content pages are intended for authors to incorporate reviewer feedback and enhance the quality of their papers, and only the References and Appendix can go into the remaining following pages (with the corresponding page limits). Any regular and required sections have to stay within the main content pages.
All papers to be published and included in the proceedings need to meet the requirements of the camera-ready format required by ACM. Camera-ready versions of accepted papers can and should include all information to identify authors, and should acknowledge any funding received that directly supported the presented research. Such information should also stay within the main content pages. The rights retained by authors who transfer copyright to ACM can be found here.
Reproducibility. In their submission, authors may refer to online code repositories such as a GitHub repository, though not strictly required, it is highly recommended. After the submission deadline, there will be no further opportunity to share this with reviewers during the review process, as rebuttals and discussions will not allow hyperlinks.
Upon acceptance, authors are strongly encouraged to make their code and data publicly available. We are promoting the use of the “Artifacts Available” badge in ACM Digital Library. If you release any code, dataset, or similar artifact to accompany your paper, and host it in a publicly available, archival repository for research artifacts that provides a Document Object Identifier (DOI), you are welcome to apply for this badge.
There will be two rounds of applications for the badge:
- Upon submission, authors can pledge that they will make their artifacts available upon publication. This pledge will be revealed to reviewers, who may consider this commitment positively. An accepted paper that later reneges on its pledge may have its acceptance retracted.
- Upon acceptance, authors who have not made such a pledge during submission, would still be welcome to apply for this badge during the camera-ready preparations.
An artifact evaluation committee will check the artifacts of all accepted papers for availability and relatedness to the paper after the acceptance notification.
Registration. To be included in the conference program (and proceedings where it applies), every accepted paper must be covered by a distinct conference registration, e.g., two multi-authored papers require two registrations, even if they have overlapping authors. This registration must be Full Conference (5-day) registration, at the standard (non-student) in-person rate, payment of which must be completed by the specified deadline. This registration requirement applies universally, regardless of attendance or presentation mode.
Presentation. Every accepted paper must be presented at the conference. Oral presentations will be selected only for high-quality accepted full papers, while all other accepted papers will be presented as posters. No-show papers may be withdrawn from the conference program (and proceedings where it applies).
Official Publication Date. The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2026 will be confirmed at a later stage. The official publication date affects the deadline for any patent filings related to published work.
Important update on ACM’s new open access publishing model for 2026 ACM Conferences!
Starting January 1, 2026, ACM will fully transition to Open Access. All ACM publications, including those from ACM-sponsored conferences, will be 100% Open Access. Authors will have two primary options for publishing Open Access articles with ACM: the ACM Open institutional model or by paying Article Processing Charges (APCs). With over 1,800 institutions already part of ACM Open, the majority of ACM-sponsored conference papers will not require APCs from authors or conferences (currently, around 70-75%).
Authors from institutions not participating in ACM Open will need to pay an APC to publish their papers, unless they qualify for a financial or discretionary waiver. To find out whether an APC applies to your article, please consult the list of participating institutions in ACM Open and review the APC Waivers and Discounts Policy. Keep in mind that waivers are rare and are granted based on specific criteria set by ACM.
Understanding that this change could present financial challenges, ACM has approved a temporary subsidy for 2026 to ease the transition and allow more time for institutions to join ACM Open. The subsidy will offer:
- $250 APC for ACM/SIG members
- $350 for non-members
This represents a 65% discount, funded directly by ACM. Authors are encouraged to help advocate for their institutions to join ACM Open during this transition period.
This temporary subsidized pricing will apply to all conferences scheduled for 2026.
AI4Sciences Program Committee Chairs
Email: kdd-ai4sciences-chairs@acm.org
Carl Yang (Emory University)
Leman Akoglu (Carnegie Mellon University)
