My research interests embrace the following topics in the area of Business Process Management:
- management of large collections of business process models
- variability management in business process families
- process mining
- process configuration
- process modelling and automation
The updated list of my publications can be found here. Some of my publications (full-text) are also available from BPMCenter and from the QUT ePrints archives. Citations to my work can be found on Google Scholar profile.
Some of my research output is showcased in the following sites:
: an open and extensible platform for the storage and disclosure of process models of a variety of languages and abstractions levels. AProMoRe provides advanced functionality for the design, evaluation, filtering and presentation of large collections of process models.
: research findings and experiences in the area of business process configuration that have mainly been obtained through my PhD.
: a fully-featured open-source workflow management system based on the workflow patterns and built on a service-oriented architecture.
: a workflow system that extends the YAWL system to support the automation of film production processes.
I am or was involved in the following research projects:
- ARC Discovery Grant "Improved Business Decision-Making via Liquid Process Model Collections" (Australia): This project will develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project will capitalize on the value hidden in large process data, as recorded in event logs. The approach will be implemented in an open-source technology to facilitate advanced investigations and predictions that can ultimately lead to better strategic decision-making. This technology also has the potential to become a research-enabling tool for the large research community in business process management.
- ARC Discovery Grant "Risk-Aware Business Process Management" (Australia): this project will unify the fields of risk management and business process management, providing a
conceptual foundation for risk-aware business processes and defining best practices in their design and
deployment. This first-time integration of risk and process management will lead to profound impact in an
important area, as recent risk control and process failures show (e.g., NAB trading scandal, Heathrow
Terminal 5). The project will use sound theoretical foundations and empirical evaluations to deliver a range of
techniques, tools and practices for recognising and managing risk in business processes. These outcomes
will have broad applicability and uptake in a wide range of industries.
- ARC Linkage Project "Facilitating Business Process Standardization and Reuse" (Australia): Business Process Management (BPM) is a recognised number one priority for Australian organisations.
Successful BPM relies on the existence of advanced repositories providing access to graphical process
models. However, current solutions have severe limitations in terms of reuse and standardisation of best
process practices. This project will a) develop and validate an innovative, open-source platform to support the reuse and standardisation of best process practices, and b) specify appropriate governance structures
for its use. The application of this solution in the challenging context of one of Australia’s largest insurance
providers will lead to a robust and scalable contribution to one of the most pressing management challenges.
- CRC "Smart Services" (Australia): this is a research and development partnership between six major industry players and six Australian universities, funded by the private sector and the government under the Australian Government’s Cooperative Research Centre program. Its aim is the creation of research-enabled commercial outcomes for its partners. Within this project, I investigate techniques for process model rationalization in the context of large collections of process models.
- Jacquard project "CoSeLoG - Configurable Services for Local Governments" (Netherlands): this project aims to create a cloud infrastructure for municipalities. Such a cloud would offer services for handling various types of permits, taxes, certificates, and licenses. Although municipalities are similar, their internal processes are typically different. Within the constraints of national laws and regulations, municipalities can differentiate because of differences in size, demographics, problems, and policies. Therefore, the cloud should provide configurable services such that products and processes can be customized while sharing a common infrastructure.
- ARC Discovery Grant "Next Generation Reference Process Models" (Australia): this project partly supported my PhD study and is later my Senior Research Fellow position. It investigates techniques for increasing the productivity of business process analysts by allowing them to reuse as much as possible existing models rather than systematically desigining new ones from scratch. Specifically, as part of my PhD, I developed a language for designing highly configurable process models (involving multiple process perspectives), a questionnaire-based approach for its configuration and investigated correctness issues related to process configuration in the context of Petri Net and YAWL.
- ARC Centre of Excellence for Creative Industries and Innovations "BPM for the Creative Industries" (Australia): this project investigates the application of BPM technology to the field of screen business and its derived benefits. As part of my PhD, I developed and validated several case studies with the help of domain experts from the Australian Film Television & Radio School, and worked on a configurable reference process model for Post Production. As part of the YAWL Initiative, I worked on the development and deployment of the YAWL4Film platform, which aims to automate the production process.