The First International Workshop on Generative AI for Process Mining (co-located with ICPM 2024)
Technical University of Denmark, Copenhagen, October 14, 2024
Generative AI is a powerful tool for a multitude of activities, and prototypes implementing GenAI in process analyses have been recently proposed by industry and academia. However, while basic use cases are being covered, more advanced and systematic studies need to be discussed. Moreover, while prototypes have been implemented, their effectiveness in terms of improving a company’s KPI was marginally discussed.
This workshop wants to discuss novel results, methodologies, and case studies on the topic of GenAI in process mining. The discussion is open to short, medium, and long-term goals.
This workshop aims to connect companies willing to implement GenAI in the analysis, improvement and execution of their business processes with researchers and organizations prototyping and implementing such integration. Also, we aim to propose and stimulate the integration of GenAI with other advanced technologies (blockchain, RPA, BPM systems).
The Technical University of Denmark (DTU) is proud to host ICPM 2024 and looks forward to welcoming attendees to our campus, which is situated to the north of Copenhagen, near Lyngby.
We aim to receive submissions of different types:
Full 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, we are expected to have an acceptance rate for papers published in LNBIP of not more than 50%.
We aim to accept papers targeting GenAI for process mining, including but not limited to:
The submissions to the workshop should be made via Easychair: https://easychair.org/conferences/?conf=icpm2024
We aim to open the workshop with a keynote of an experienced professional explaining the current state of the usage of GenAI in process mining and short/medium/long-term objectives.
Then, the accepted papers will be discussed in different sessions. At the end of each session, a short Q&A session will be implemented to foster discussion.
The workshop will be concluded by a round table session in which the attendants will provide their ideas on the evolution of GenAI4PM.
Maxim Vidgof is an Assistant Professor at Vienna University of Economics and Business, specializing in process mining and process automation. His doctoral research was centered on the complexity of business processes, aiming to develop new methodologies for understanding and managing this complexity. His current research interests include examining process complexity and the application of Large Language Models in Business Process Management.
Alessandro Berti is a Ph.D. student at RWTH Aachen University, affiliated with the Process and Data Science (PADS) group. His doctoral thesis focuses on object-centric process mining. He plays a role as the main developer of pm4py, a leading Python library for process mining. Alessandro has made significant contributions to the integration of large language models within the pm4py framework. His work includes both development and research, with some publications that bridge the gap between large language models and the field of process mining.
Mohammadreza Fani Sani is an accomplished Applied and Data Scientist at Microsoft, with a strong academic background in Process and Data Science from RWTH Aachen University. His doctoral research was conducted within the Process and Data Science (PADS) group, where he focused on preprocessing data to enhance the performance of process mining applications. Currently, his work at Microsoft involves productizing Large Language Models for Copilot AI and Process Mining. With his blend of academic expertise and industry experience, Mohammadreza is making strides in the integration of large language models in the field of process mining.
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