Enterprises continue to move towards automating business processes as they seek to be more cost-effective, reliable, and scalable. Technology-infused services enable them to reduce direct and indirect costs while also reducing human errors and improving productivity. In recent times, Business Process Automation has become an effective way to achieve these goals. The latest trends in automating business processes center around process digitization, process standardization, data integrity checks, workflow automation including robotic process automation, and generating actionable reports, views & interfaces to empower the end-user. The next wave of technology advancements will transform business processes by leveraging recent advances in AI, including Analytics/Machine Learning (ML), Optimization methods, and Automation. The workshop will focus on the theme of advanced AI (including analytics, automation, and optimization) for the transformation of core enterprise processes as well as for other processes, such as Information Technology (IT) processes and software development processes. Both research (theoretical or applied) and real-world application papers are welcome.
The workshop will focus on the theme of applying AI for enterprise process transformation which includes advanced methods for analytics, automation and optimization. Enterprise processes include core business processes as well as other processes such as Information Technology (IT) processes and software development processes, with increasing digitization and automation. Both research (theoretical or applied) and real-world application papers are welcome.
Authors are invited to submit original, previously unpublished research papers. We will accept different types of contributions:
Papers should be written in English, following Springer LNCS style including all text, references, appendices, and figures. Since it is single blind review process, please include author names and affiliations. For formatting instructions and templates, see the Springer Web page: http://www.springer.de/comp/lncs/authors.html. Submitted papers will be evaluated by at least three members of the international program committee. At least one author of each accepted paper must register and participate in the workshop to present the paper. The workshop papers will be included in a LNCS/LNAI post Proceedings of PAKDD Workshops published by Springer .
Submissions should be made via the Easychair system through the AI4EPT submission page available here: https://easychair.org/conferences/?conf=ai4ept2021 (select the track "Workshop on Artificial Intelligence for Enterprise Process Transformation).
The submitted papers must not be previously published anywhere and must not be under consideration by any other conference or journal during the AI4EPT review process.
Professor of Computer Science at Macquarie University, Australia
Founder and CEO, Technovisor AI
Artificial Process Intelligence: AI for Process Automation and Transformation in the Enterprise
Hamid R. Motahari-Nezhad is a technology visionary, innovator and a science scholar with a focus in Artificial Intelligence, Enterprise AI and Business Process Management. He is holding an Honorary Professor of Computer Science position at Department of Computing at Macquarie University, Australia. Most recently, Hamid served as Head of AI Science at EY AI Lab, Palo Alto, in EY Global Technology Innovation where he was leading the global AI Science team working in Document Intelligence and Enterprise AI. His background and interest lies in applied AI, document intelligence, conversational AI, intelligent RPA, and AI in business process management and transformation. Prior to that Hamid was the Research Lead for Cognitive Services at IBM Research, and a member of IBM Academy of Technology, where his research work was focused on cognitive computing, document understanding, cognitive business processes and conversation understanding. He has published more than 100 scholarly papers in various conferences in AI, Web, Business Process Management, IT Services, and in IEEE/ACM journals. Hamid has chaired and organized various events in IEEE, ACM, AAAI, KDD, NeurIPS, BPM, ICSOC and INFORMS conferences and workshops.
Professor of Information Systems at University of Tartu, Estonia
Co-founder of Apromore
Process Mining 2.0: From Insights to Actions
Marlon Dumas is a Professor of Information Systems at University of Tartu, Estonia and co-founder of Apromore - a company dedicated to developing open-source process mining solutions. His research focuses on data-driven methods for business process management, including process mining and predictive process monitoring. He is currently recipient of an Advanced Grant from the European Research Council with the mission of developing algorithms for automated identification and assessment of business process improvement opportunities from execution data via AI techniques. During his career, he has published over 200 research publications, 10 US/EU patents, and a textbook (Fundamentals of Business Process Management) used in over 300 universities worldwide.
|14:00 - 14:10||Opening Remarks|
|14:10 - 15:10||Keynote by Prof. Hamid Motahari|
|15:10 - 15:30||Paper 1: "ROC Bot: Towards Designing Virtual Command Centre for Energy Management"|
|15:30 - 15:45||Coffee Break|
|15:45 - 16:45||Keynote by Prof. Marlon Dumas on "Process Mining 2.0: From Insights to Actions"|
|16:45 - 17:05||Paper 2: "Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams"|
|17:05 - 17:30||Closing Remarks and Networking|