IMPORTANT DATES

• Abstract submission: Sep 4, 2026 (AoE) (mandatory)

• Paper submission: Sep 11, 2026 (AoE)

• Notification to authors: Nov 4, 2026

• Camera-ready submission: Nov 25, 2026

• Conference start: Feb 8, 2027 

TOPICS OF INTEREST

Topics of interest may include but are not limited to:

• Machine Learning for Process Discovery

• AI Driven Monitoring Business Process

• Prescriptive Process Analytics

• Process Recommendation Systems

• Agentic AI for Process Improvement

• LLMs for Process Mining

• Explainability of AI Decision Processes

• Monitoring AI-driven Business Processes

• Process Intelligence Platforms

• Federated Process Mining

• Privacy-Preserving Process Discovery

• Secure Process Analytics

• Healthcare Process Mining

• Manufacturing and Industry 5.0

• Smart Cities

• Agriculture

• Transportation and Logistics

• Public Sector Processes

• Education Analytics

INSTRUCTIONS FOR SUBMISSION

Contributions to all calls should be submitted electronically to the Workshop management system connecting to https://easychair.org/my/conference?conf=icpm2027. 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 40%.

Authors are requested to prepare submissions according to the format of the Lecture Notes in Business Information Processing (LNBIP) series by Springer https://link.springer.com/series/558/information-for-authors-and-editors.

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.

Registrations are managed by the ICPM system