In conjunction with the International Conference on Process Mining (ICPM 2027)
A leading workshop dedicated to process discovery, conformance checking, business process intelligence, formal process modeling, process analytics, and descriptive process mining research.
Business Process Intelligence (BPI) refers to the application of data- and process-mining techniques in the field of Business Process Management. BPI is an area that spans process mining, process discovery, conformance checking, predictive analytics and many other techniques that are all gaining interest and importance in industry and research. In practice, BPI is embodied in tools for managing process execution by offering several features such as analysis, prediction, monitoring, control, and optimization.
The workshop aims at discussing the current state of ongoing research and sharing practical experiences, exchanging ideas and setting up future research directions. We aim to bring together practitioners and researchers from different communities such as business process management, information systems, business administration, software engineering, artificial intelligence, process mining, and data mining who share an interest in the analysis of business processes and process-aware information systems.
The call for papers of the workshop is aligned with the call for papers of ML4PM where we encourage to refrain from submitting to BPI on the topics of machine and deep learning approaches for predictive and prescriptive purposes (and vice versa). BPI continues its well-established lineage of dissemination of descriptive and verification-oriented process mining approaches as listed in the topics of in the tentative call for papers.
The BPI Challenge returns for its 11th edition.
Participants will analyze a real-life object-centric dataset collected using the open-source GitHub scraping framework PyStackT.
The challenge aims to showcase state-of-the-art process mining tools and techniques while providing a reusable benchmark dataset for object-centric process mining research.
The three best teams will present their work during the workshop and compete for the BPI Challenge award.
November 11, 2026 (AoE)
November 18, 2026 (AoE)
December 21, 2026 (AoE)
January 21, 2027 (AoE)
February 8, 2027
February 22, 2027
Submissions must use the Springer LNCS/LNBIP format (author guidelines). Papers must be written in English and cannot exceed 12 pages, including tables, figures, references, and appendices.
Each paper should contain a short abstract clarifying its relation to the workshop topics, clearly stating the problem being addressed, the goal of the work, the results achieved, and its relation to existing work.
Papers should be submitted electronically as a self-contained PDF via the submission system:
https://easychair.org/conferences/?conf=icpm2027
When submitting your paper in the submission system, please select the workshop track "BPI 2027 – Business Process Intelligence".
Submissions must be original contributions that have not been published previously and must not be simultaneously under review for any other conference, workshop, or journal.
Submitted papers will be evaluated based on significance, originality, and technical quality. Members of the program committee will review all submissions. Authors are encouraged to indicate whether the data and software used in their work are publicly available and, if so, provide links to the corresponding repositories.
Springer will publish all accepted workshop papers in a post-workshop proceedings volume in the Lecture Notes in Business Information Processing (LNBIP) series.
At least one author of each accepted paper must register for and participate in the workshop. Additional information regarding registration and attendance is available on the ICPM 2027 conference website:
Associate Professor
Technical University of Denmark (DTU)
Associate Professor
KU Leuven, Belgium
Assistant Professor
Eindhoven University of Technology (TU/e)