Professor Moe Thandar Wynn

  • Professor Moe Thandar Wynn

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Co-Leader, Data for Discovery Research Program; Professor, School of Information Systems

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:

  • 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 110+ refereed research papers including 40+ journal articles, 40+ refereed conference papers.
  • Attracted external funds for QUT in excess of AUD $5 million as a chief investigator across 22 research programs since 2011
  • Google h-index: 36, 6000+ citations; Scopus h-index: 27, 3000+ citations (March 2023)
  • Vice-chair and a steering committee member within IEEE task Force on Process Mining
  • Co-leader, Data for Discovery Theme, QUT's Tier 1 Centre for Data Science
  • Research interests: Process Mining, Process Automation, Data Quality, Robotic process automation, Business process analytics (simulation, monitoring, mining), Workflow patterns and Yet Another Workflow Language, Petri nets and Reset nets

Prof Wynn leads the Process Science Academic Program (formerly Business Process Management) and is  Academic Lead of Research for the School of Information Systems, Queensland University of Technology. She co-leads the Data for Discovery Program within QUT’s Centre for Data Science and the Digital Health Initiative within 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).

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 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).

Prof Wynn was recognised as a recipient of QUT Vice-Chancellor’s Excellence Award (individual) for exceptional sustained performance and outstanding achievement in two categories (Research, Partnerships and Engagement), 2018 and a recipient of QUT Vice-Chancellor’s Excellence Award (individual) for research excellence in 2022.

Additional information

Experience

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

Awards

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
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.
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
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.

Publications

Research Projects

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

Current Supervisions

Completed Supervisions (Doctorate)

Completed Supervisions (Masters by Research)