European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECMLPKDD 2025
will be held in Porto, Portugal, from 15th and 19th of September of 2025

Conference website: https://ecmlpkdd.org/2025/

Call for Research Track Papers

The Research Track solicits high-quality research papers in all fields of Machine Learning, Knowledge Discovery, and Data Mining. Papers should demonstrate that they make a substantial contribution to the field (e.g., improve the state-of-the-art or provide new theoretical insights) and will be evaluated based on their contribution to the state of the art, technical excellence, potential impact, and clarity.

Research Track webpage: https://ecmlpkdd.org/2025/submissions-research-track/

Key Dates and Deadlines

CMT Opening: 2025-02-07
Abstract Submission: 2025-03-07
Paper Submission: 2025-03-14
Author Notification: 2025-05-26
CRC Submission: 2025-06-13


Paper Format

Papers must be written in English and formatted in LaTeX, following the outline of our author kit. The kit includes a readme document, a LaTeX file template containing author instructions, and style files. The maximum length of papers is 16 pages (including references) in this format. The program chairs reserve the right to reject any over-length papers without review. Papers that ‘cheat’ the page limit by, including but not limited to, using smaller than specified margins or font sizes will also be treated as over-length. Note that, for example, negative vspaces are also not allowed by the formatting guidelines; further details can be found in the author kit. Up to 10 MB of additional materials (e.g., proofs, audio, images, video, data, or source code) can be uploaded with your submission.If there is an appendix, ensure it is submitted separately from your paper, which must adhere to the 16-page limit.The reviewers and the program committee reserve the right to judge the paper solely on the basis of the 16 pages of the paper; looking at any additional material is at the discretion of the reviewers and is not required.

Authorship

The author list as submitted with the paper is considered final. No changes to this list may be made after paper submission, either during the review period, or in case of acceptance, at the final camera-ready stage.

Double-blind Review

Similarly to previous years, we will apply a double-blind review-process (author identities are not known by reviewers or area chairs; reviewers do see each other’s names). All papers need to be ‘best-effort’ anonymized. Papers must not include identifying information of the authors (names, affiliations, etc.), self-references, or links (e.g., GitHub, YouTube) that reveal the authors’ identities (e.g., references to own work should be given neutrally like other references, not mentioning ‘our previous work’ or similar). We strongly encourage making code and data available anonymously (e.g., in an anonymous Github repository, or Dropbox folder). The authors might have a (non-anonymous) pre-print published online, but it should not be cited in the submitted paper to preserve anonymity. Reviewers will be asked not to search for them. We recognize there are limits to what is feasible with respect to anonymization. For example, if you use data from your own organization and it is relevant to the paper to name this organization, you may do so.

Submission Process

Electronic submissions will be handled via CMT available here: https://cmt3.research.microsoft.com/ECMLPKDD2025/. Submissions will be evaluated by three reviewers on the basis of novelty, technical quality, potential impact, and clarity.

Conference Attendance

For each accepted paper, at least one author must register for the main conference and present the paper in person.

Proceedings

The conference proceedings will be published by Springer in the Lecture Notes in Computer Science Series (LNCS).

Reproducible Research Papers

Authors are strongly encouraged to adhere to the best practices of Reproducible Research, by making available data and software tools that would enable others to reproduce the results reported in their papers. We advise the use of standard repository hosting services such as Dataverse, mldata.org, OpenML, figshare, or Zenodo for data sets, and mloss.org, Bitbucket, GitHub, or figshare (where it is possible to assign a DOI) for source code. If data or code gets updated after the paper is published, it is important to enable researchers to access the versions that were used to produce the results reported in the paper. Authors who do not have a preferred repository are advised to consult Springer Nature’s list of recommended repositories and research data policy.

Ethics Considerations

Ethics is one of the most important topics to emerge in Machine Learning, Knowledge Discovery and Data Mining. We ask you to think about the ethical implications of your submission – such as those related to the collection and processing of personal data or the inference of personal information, the potential use of your work for policing or the military. You will be asked in the submission form about the ethical implications of your work which will be taken into consideration by the reviewers.

Authors Commit to Reviewing

Authors of submitted papers agree to provide the email address of at least one author who holds a PhD to be a potential PC member for ECML PKDD 2025 and may be asked to review papers for the conference if we have many more submissions than expected. This does not apply to authors who are (a) already contributing to ECML PKDD (e.g., accepted a PC/AC invite, are part of the organizing committee) or (b) not qualified to be ECML PKDD PC members (e.g., limited background in ML or DM).

Dual Submission Policy

Papers submitted should report original work. Papers that are identical or substantially similar to papers that have been published or submitted elsewhere may not be submitted to ECML PKDD, and the organizers will reject such papers without review. Authors are also NOT allowed to submit or have submitted their papers elsewhere during the review period. Submitting unpublished technical reports available online (such as on arXiv), or papers presented in workshops without formal proceedings, is allowed, but such reports or presentations should not be cited to preserve anonymity.

Conflict of Interest

During the submission process, you must enter the email domains of all institutions with which you have an institutional conflict of interest. You have an institutional conflict of interest if you are currently employed or have been employed by that institution in the past three years, or you have extensively collaborated with the institution within the past three years. Authors should also identify other conflicts of interest, such as co-authorship in the last five years, colleagues in the same institution within the last three years, and advisor/student relations (anytime in the past).

Contact

For further information, please contact Mail: ecml-pkdd-2025-research-track@googlegroups.com