Call for Papers
The goal of the AI4BPM workshop is to provide a forum for researchers and professionals interested in understanding, envisioning and discussing the challenges and opportunities of moving from current, largely programmatic approaches for BPM, to emerging forms of AI-enabled BPM. We invite you to submit original papers to be considered for inclusion in the workshop.
Topics of interest
This workshop encourages papers describing original research and industrial experiences that explore how AI can be applied in BPM contexts. The workshop takes a broad view of both AI and BPM.
The workshop is interested in applications of AI for BPM, ranging from improvements on traditional approaches to BPM to fundamental transformations in how business operates. This may include (but is not limited to) the following:
- Machine Learning, including Deep Learning, to support workflow management
- Process Mining augmented with AI techniques
- Natural Language Processing in Business Process Management
- Recommender Systems for business processes
- Constrain-based reasoning
- Automation of exception handling
- Agent-Based Modeling and Simulation for BPM
- Virtual Assistants to simplify interaction with processes
- Goal-driven approaches to process management
- Knowledge Representation, management and reasoning on process specifications
- Ontology-driven BPM
- AI technology for BPM-related standards such as BPMN, CMMN and DMN
- Application of AI to (Data-Driven) BPM
- AI-based robotic process automation
- AI-driven modeling and optimization of business processes
- AI enablement for declarative and hybrid models
- AI-based enrichment of IoT-enabled processes
- Applications of Automated Planning techniques for BPM
- Applications of AI for Blockchain-hosted processes
- Applications of AI in industry-specific business processes (retail, e-commerce, finance, manufacturing, healthcare)
- Non-traditional models and approaches to BPM that leverage AI
- Social, economic, and business impacts of infusing AI into BPM
Given that the research area of AI for BPM is in its infancy, we especially encourage submissions that explore totally new directions, which step outside of the areas listed above.
Submissions: type and content
The activities of the workshop will include presentations of scientific papers and experience reports, and also discussion sessions. We solicit three kinds of submission:
- Research papers, up to 12 pages, describing original and novel research work, including research results and evaluations. Research papers should not have been published or submitted for publication concurrently elsewhere.
- Experience papers, up to 12 pages, describing experiences with the novel application of AI techniques to BPM. Such papers should include clear descriptions of the motivations underlying the use of AI for BPM, the value obtained through the use of AI, and the challenges that needed to be overcome. Experience papers should not have been published or submitted for publication concurrently elsewhere.
- Challenge Statements, at least 4 and up to 6 pages, presenting a position on issues related to the topics of the workshop. These statements would lead to interesting discussion by raising key questions, controversial point of views, challenges, and ideas to address the identified issues.
Papers should be written in English, following the Springer LNCS format. All submissions will be reviewed by the workshop organizers and selected PC members. The submission process will be managed using the Easychair conference management system. Depending on the quality of submissions, we also consider publishing long versions of papers and challenge statements in a special issue of the Journal on Data Semantics.
- Workshop papers submission deadline:
May 29, 2020June 12, 2020 - AI4BPM submission page available here (select the track "Workshop on Artificial Intelligence for Business Process Management").
- Workshop papers notification deadline:
June 29, 2020July 6, 2020
- Workshop camera-ready papers deadline: July 13, 2020
- Workshop date: September 14, 2020