The International Workshop on Leveraging Machine Learning in Process Mining - ML4PM - is a premier event that aims to foster collaboration and innovation in the intersection of machine learning and process mining. Over the past few years, the combination of these two fields has generated a lot of interest, and this workshop provides an excellent opportunity for researchers and practitioners to share their latest findings and explore new directions for future research.
The workshop will feature a diverse range of papers that showcase the latest advances in automated process modelling, predictive process mining, deep learning techniques, and online process mining. These themes reflect the most exciting and promising areas of research at the intersection of machine learning and process mining. By fostering dialogue and collaboration among participants, the workshop aims to catalyze breakthroughs and push the boundaries of what is possible in this exciting and rapidly-evolving field.
ML4PM 2025 will be held in Montevideo, in conjunction with the ICPM conference.
This workshop invites papers that present works that lay in the intersection between machine learning and process mining. The event provides a suitable environment to discuss new approaches presented by researchers and practitioners. Main themes include automated process modeling, predictive process mining, application of deep learning techniques and online process mining. The workshop will count with leading researchers, engineers and scientists who are actively working on these topics.
Topics of interest for submission include, but are not limited to:
Contributions to all calls should be submitted electronically to the Workshop management system connecting to https://easychair.org/my/conference?conf=icpm2025. At least one author of each accepted paper is expected to participate in the conference and present his/her work.
Submissions must be original contributions that have not been published previously. Submissions must be in English and must not exceed 12 pages (including figures, bibliography and appendices). Each paper should contain a short abstract, clarifying the relation of the paper with the workshop topics, clearly state the problem being addressed, the goal of the work, the results achieved, and the relation to the literature. Research papers will be published by Springer as a post-workshop proceedings volume in the series Lecture Notes in Business Information Processing (LNBIP). Due to editorial requirements, traditional workshops are expected to have an acceptance rate for research papers published in the LNBIP series of not more than 50%.
Authors are requested to prepare submissions according to the format of the Lecture Notes in Business Information Processing (LNBIP) series by Springer http://www.springer.com/computer/lncs?SGWID=0-164-6-791344-0.
We encourage authors to follow the principles of transparency, reproducibility, and replicability. To enhance the accessibility of research artifacts and datasets, authors are advised to make them accessible via public repositories (e.g., Zenodo, Figshare, GitHub, or institutional archives) under an open data license such as the CC0 dedication or the CC-BY 4.0 license.
The authors of selected regular papers may be invited to submit an extended version of their contributions to the Process Science journal.
Registrations are managed by the ICPM system
| Milestone | Deadline |
|---|---|
| Abstract Submission | |
| Paper Submission | |
| Notification of Acceptance | August 22, 2025 |
| Submission of Camera Ready Papers | September 22, 2025 |
| Workshop | October 20, 2025 |
| Post-workshop Camera-Ready Papers | November 4, 2025 |
