Doctor of Philosophy (Queensland University of Technology), Master of Information Technology (Research) (Queensland University of Technology)
Research theme: Information;
Research discipline: Information Systems
Researcher Profile:
- Co-Director, QUT's Centre for Data Science
- Awarded a PhD on the topic of "Semantics, Verification, and Implementation of Workflows with Cancellation Regions and OR-joins" from QUT in Nov 2006
- Published 150+ refereed research papers including 45+ journal articles, and 50+ refereed conference papers.
- Attracted external funds for QUT in excess of AUD 6 million as a chief investigator across 28 research programs since 2011
- Google h-index: 41, 8700+ citations; Scopus h-index: 32, 4700+ citations (January 2025)
- Vice-chair and a steering committee member within the IEEE Task Force on Process Mining (2019 - 2023)
- Research interests: Process Mining, Process Automation, Data Quality, Data Mining, Robotic process automation, Business process analytics (simulation, monitoring, mining), Workflow patterns and Yet Another Workflow Language, Petri nets and Reset nets
Prof Wynn is the Co-Director of QUT Centre for Data Science. She leads the Process Science Academic Program (formerly Business Process Management) and is the Academic Lead of Research for the School of Information Systems. She has been appointed as a member of the Australian Research Council College of Experts for the period of 3 years (2023 – 2025).
Prof Wynn conducts research in the areas of business process management, workflow management, process mining and data quality, having completed her PhD in workflow management, and process automation. She is recognised internationally for her contributions to the formal foundations of process modelling, verification, automation, and process-oriented data mining (process mining).
As an international BPM researcher and educator, Prof Wynn has served as a co-chair for conferences and workshops, program committee member for international conferences, grant assessor for the ARC research council, PhD thesis examiner, and a reviewer of international journals. She was a program committee chair of the 2nd International Conference on Process Mining 2020 and the International Conference on Business Process Management 2021 and was invited as an expert member to contribute to the CRC Food Agility: Mission Food for Life 2020 project. She was a co-editor of a special Issue on Robotic Process Automation (RPA) in the Computers in Industry Journal (2021) and is a co-editor of a special Issue on Managing the Dynamics of Business Processes in the Business & Information Systems Engineering journal (2023-2024).
Prof Wynn was recognised as the recipient of the QLD Women in Technology Excellence in Research Award (2024). She is a recipient of the QUT Vice-Chancellor’s Excellence Award (individual) for exceptional sustained performance and outstanding achievement in two categories (Research, Partnerships and Engagement), in 2018 and a recipient of the QUT Vice-Chancellor’s Excellence Award (individual) for research excellence in 2022.
Additional information
Prof Wynn has extensive knowledge of information systems, data architecture, data quality, workflow technologies and process-oriented data mining. She has over fifteen years of experience in conducting applied research across multiple Australian sectors engaging with logistics, healthcare, insurance, utility, education, government, mining, and agri-food supply chains to pinpoint inefficiencies and derive data-driven improvements.
- Type
- Membership of Review Panels on Prestigious Grant Applications
- Reference year
- 2023
- Details
- Member of the ARC College of Experts (2023 - 2025)
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2022
- Details
- QUT Vice-Chancellor's Excellence Award (Research)
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2019
- Details
- I am a recipient of QUT Vice-Chancellor's Excellence Award (individual) for exceptional sustained performance and outstanding achievement in two categories (Research, Partnerships and Engagement) in 2018.
- Type
- Advisor/Consultant for Industry
- Reference year
- 2019
- Details
- I am a pioneer in delivering impactful outcomes using research-informed process-oriented data mining (process mining) techniques for Australian industry stakeholders. I have already supported Australian stakeholders, in a range of sectors including healthcare, insurance, utility, retail, government and education to pinpoint inefficiencies and derive concrete performance improvements.
- Type
- Other
- Reference year
- 2019
- Details
- I am a steering committee member of the IEEE Taskforce on Process Mining. I am a working group member of the IEEE standardisation of eXtensible Event Stream (XES) and involved in approving XES certification of commercial and open-source process mining tools.
- Suriadi, S., Andrews, R., ter Hofstede, A. & Wynn, M. (2017). Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs. Information Systems, 64, 132–150. https://eprints.qut.edu.au/97670
- Ter Hofstede, A., Koschmider, A., Marrella, A., Andrews, R., Fischer, D., Sadeghianasl, S., Wynn, M., Comuzzi, M., De Weerdt, J., Goel, K., Martin, N. & Soffer, P. (2023). Process-Data Quality: The True Frontier of Process Mining. Journal of Data and Information Quality, 15(3). https://eprints.qut.edu.au/244538
- Fehrer, T., Fischer, D., Leemans, S., Roeglinger, M. & Wynn, M. (2022). An assisted approach to business process redesign. Decision Support Systems, 156. https://eprints.qut.edu.au/228761
- Goel, K., Leemans, S., Martin, N. & Wynn, M. (2022). Quality-Informed Process Mining: A Case for Standardised Data Quality Annotations. ACM Transactions on Knowledge Discovery from Data, 16(5). https://eprints.qut.edu.au/228478
- Pika, A., Leyer, M., Wynn, M., Fidge, C., ter Hofstede, A. & van der Aalst, W. (2017). Mining resource profiles from event logs. ACM Transactions on Management Information Systems, 8(1). https://eprints.qut.edu.au/80195
- Burke, A., Leemans, S., Wynn, M., van der Aalst, W. & ter Hofstede, A. (2024). A chance for models to show their quality: Stochastic process model-log dimensions. Information Systems, 124. https://eprints.qut.edu.au/249229
- Egger, A., ter Hofstede, A., Kratsch, W., Leemans, S., Roeglinger, M. & Wynn, M. (2024). Bot log mining: An approach to the integrated analysis of Robotic Process Automation and process mining. Information Systems, 126. https://eprints.qut.edu.au/251622
- Mamudu, A., Bandara, W., Wynn, M. & Leemans, S. (2024). Process Mining Success Factors and Their Interrelationships. Business and Information Systems Engineering. https://eprints.qut.edu.au/247292
- Duwalage, K., Wynn, M., Mengersen, K., Nyholt, D., Perrin, D. & Robert, P. (2023). Predicting Carcass Weight of Grass-Fed Beef Cattle before Slaughter Using Statistical Modelling. Animals, 13(12). https://eprints.qut.edu.au/242584
- Kapugama Geeganage, D., Wynn, M. & ter Hofstede, A. (2024). Text2EL+: Expert Guided Event Log Enrichment using Unstructured Text. Journal of Data and Information Quality, 16(1). https://eprints.qut.edu.au/245822
- Title
- Mathematical Decision Support to Optimise Hospital Capacity and Utilisation
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP180100542
- Start year
- 2020
- Keywords
- Title
- Improved Business Decision-Making via Liquid Process Model Collections
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP150103356
- Start year
- 2015
- Keywords
- process mining; process model collection; business process management
- Title
- Cost-aware business process management
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP120101624
- Start year
- 2012
- Keywords
- Information System; Business Process Model; Workflow Management; Management Accounting
- Title
- Reducing variation in clinical practice: a twin track approach to support improved performance
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- Start year
- 2012
- Keywords
- Clinical Practice; Cost-Effectiveness; Performance; Process Mining
- Title
- Risk-Aware Business Process Management
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP110100091
- Start year
- 2011
- Keywords
- Risk Management; Information System; Business Process Model; Workflow Management
- Process Mining with Exogenous Data
PhD, Principal Supervisor
Other supervisors: Dr Sander Leemans, Dr Robert Andrews - Improving Object-Centric Event Log Generation Through Visual Analytics and AI
PhD, Associate Supervisor
Other supervisors: Professor Arthur ter Hofstede - Quality Drift in Process Event Streams
PhD, Principal Supervisor
Other supervisors: Professor Arthur ter Hofstede - Unveiling Dynamics Between Robotic Process Automation and Process Knowledge Loss
PhD, Mentoring Supervisor
Other supervisors: Dr Rehan Syed
- A Conceptualisation of Process Mining Impacts (2024)
- Process mining with labelled stochastic nets (2024)
- Advancing process analytics for agri-food supply chains (2023)
- The Quality Guardian: Improving Activity Label Quality in Event Logs Through Gamification (2022)
- Influence of Performance Measurements on Institutionalizing Process Improvement Initiatives (2019)
- Towards Cost Model-driven Log-based Business Process Improvement (2016)
- Evaluating Business Process Compliance Management Frameworks (2015)
- Mining Process Risks and Resource Profiles (2015)

