== CALL FOR PAPERS ==

WORKSHOP ON ARTIFICIAL INTELLIGENCE FOR BUSINESS PROCESS MANAGEMENT
http://ai4bpm.inf.unibz.it
in conjunction with the 16th Business Process Management Conference (BPM 2018)
September 9 - 14, 2018, Sydney, Australia

The field of Artificial Intelligence continues to grow, with new and deeper techniques, and with application across numerous areas. In the past few years we have seen strong interest from both industry and academia in applying AI techniques in the area of Business Process Management. Indeed, the application of AI is impacting additional areas where process management perspectives and techniques are relevant, including industrial engineering, IoT, and emergency response, to name a few. The use of AI in BPM has been discussed as the next disruptive technology that will touch almost all of the business process activities being performed by humans. In some cases AI will dramatically simplify human interaction with a process, in other cases it will extensively support humans in the execution of tasks, and in yet other cases it will enable full automation of tasks that have traditionally required manual contributions. Over time AI may lead to entirely new paradigms for business processes and operations. For example, instead of BPM models centered on process or on case management, we anticipate models that are based fundamentally on goal achievement, as well as we anticipate models that fully enable continuous improvement and adaptation based on experiential learning.

This workshop represents the union of the Business Process Innovation with Artificial Intelligence (BPAI - https://bpai.inf.unibz.it/) and the Cognitive Business Process Management (CBPM - https://sites.google.com/site/cbpm2017/) workshops. The workshop encourages papers describing original research and industrial experiences that explore how AI can be applied in BPM contexts.

AI4BPM 2018 welcomes submissions that make use of techniques coming from all areas of AI, including (but not limited to) machine learning, search, planning, knowledge representation, information extraction, reasoning, constraint satisfaction, natural language processing, robotics and perception, and multi-agent systems.


== TOPICS OF INTEREST ==

The workshop emphasizes the use of AI in across the spectrum of application areas where process management perspectives and techniques are relevant. In addition to traditional BPM contexts this includes industrial engineering, IoT applications, emergency response, autonomous systems, emerging financial models, infrastructure and technical support services, and others. The workshop topics may include (but are not limited to) the following:

- Techniques for discovering and automating tasks, processes and rules from unstructured data
- Process Mining augmented with Natural Language Understanding against unstructured data
- Knowledge representation and reasoning about process specifications and instances
- Goal-driven approaches to process management
- Virtual assistants to simplify interaction with processes
- AI-enabled creation of virtual assistant dialogues, including automated interaction with back-end systems
- Machine Learning to support automated triage and work assignment
- Machine Learning to enable automated trouble ticket resolution
- AI-enabled automation of exception handling
- Application of AI to (Data-Driven) BPM
- AI-enriched robotic process automation
- AI-enabled creation of robotic process automation solutions
- AI-driven modelling and optimization of business processes
- AI enablement for Knowledge-intensive Processes
- AI-based enrichment of IoT-enabled processes
- Applications of AI for Blockchain-hosted processes
- Applications of AI in managing industrial and manufacturing processes
- Applications of AI in industry-specific business processes (retail, e-commerce, finance, manufacturing, healthcare)
- Datasets and baselines for AI applied to BPM
- AI-enabled approaches for enhancing or transforming the BPM lifecycle
- Impact of AI technology on BPM-related standards such as BPMN, CMMN and DMN
- Non-traditional models and approaches to process management that leverage AI
- Social, economic, and business impacts of infusing AI into process management

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 ==

Accepted submissions:
- 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. The discussion session(s) will be based on one or more of the Challenge Statements received.

Papers should be written in English, following the Springer LNCS format (http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). 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: https://easychair.org/conferences/?conf=ai4bpm. 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 or a similar forum.


== IMPORTANT DATES ==

- Submission deadline: 01 June, 2018
- Notification deadline: 29 June, 2018
- Camera-ready deadline: 13 July, 2018
- Workshop: 10 September, 2018


== ORGANIZERS ==

Riccardo De Masellis, Stockholm University, Sweden
Chiara Di Francescomarino, Fondazione Bruno Kessler, Italy
Richard Hull, IBM T.J. Watson Research Center, USA
Krzysztof Kluza, AGH University of Science and Technology, Poland
Fabrizio Maria Maggi, University of Tartu, Estonia


== STEERING COMMITTEE ==

Boualem Benatallah, University of New South Wales, Australia
Chiara Ghidini, Fondazione Bruno Kessler, Italy
Marco Montali, Free University of Bolzano, Italy
Hamid R. Motahari Nezhad, Ernst and Young (EY), USA
Arik Senderovich, Technion - Israel Institute of Technology, Israel
Biplav Srivastava, IBM T.J. Watson Research Center, USA
Heiner Stuckenschmidt, University of Mannheim, Germany


== PROGRAM COMMITTEE CO-CHAIRS ==

Riccardo De Masellis, Stockholm University, Sweden
Richard Hull, IBM T.J. Watson Research Center, USA


== PROGRAM COMMITTEE ==

- Fernanda Araujo Baiao, UNIRIO, Brazil
- Amin Beheshti, Macquarie University, Australia
- Ralph Bergmann, University of Trier, Germany
- Andrea Burattin, DTU, Copenhagen, Denmark
- Fabio Casati, University of Trento, Italy
- Federico Chesani, University of Bologna, Italy
- Raffaele Conforti, University of Melbourne, Australia
- Giuseppe De Giacomo, Sapienza Università di Roma, Italy
- Claudio Di Ciccio, Vienna University of Economics and Business, Austria
- Schahram Dustdar, TU Wien, Austria
- Paolo Felli, Free University of Bolzano, Italy
- Avigdor Gal, Technion, Israel
- Aditya Ghose, University of Wollongong, Australia
- Monika Gupta, IBM India Research Lab, India
- Anup Kalia, IBM TJ Watson, USA
- Anna Leontjeva, CSIRO61, Sydney, Australia
- Henrik Leopold, VU University Amsterdam, the Netherlands
- Andrea Marrella, SAPIENZA Università di Roma, Italy
- Paola Mello, University of Bologna, Italy
- Fabio Patrizi, SAPIENZA Università di Roma, Italy
- Giulio Petrucci, Google, Switzerland
- Manfred Reichert, University of Ulm, Germany
- Niek Tax, TU/e Eindhoven, The Netherlands
- Irene Teinemaa, University of Tartu, Estonia
- Han van der Aa, VU University Amsterdam, The Netherlands
- Hagen Voelzer, IBM Zurich Research Lab, Switzerland

== MORE INFORMATION ==

Visit the workshop website http://ai4bpm.inf.unibz.it/ for detailed submission information.