Associate Professor
Chun Ouyang
Faculty of Science,
School of Information Systems
Biography
I embarked on my academic career when I joined QUT as a post-doctoral research fellow in 2004. My research interests focus on business process management (BPM) and also lie in the relevant areas such as service computing, modelling and verification using nets. In the area of BPM, my research contributes to several key disciplinary themes including business process modelling and verification, business process automation, data-driven process analytics (incl. process mining and process querying), BPM in the cloud, and more recently, robotic process automation.- I invite you to visit ‘Experience’ page for more details of my current research topics, and I welcome any genuine interest in studying or collaborating with me on the topics
- Refer to 'Publications' page for a list of my ten selected publications and to my DBLP page in computer science bibliography for my research papers and reports to date
- Refer to ‘Research projects’ page (for CAT.1 grants) and news about QUT awarded ARC grants in 2019 round
Personal details
Positions
- Associate Professor
Faculty of Science,
School of Information Systems
Keywords
Process Mining, Explainable AI, Predictive Analytics, AI Robustness, Distributed Computing, Formal Modeling and Verification (using nets)
Research field
Information Systems, Artificial Intelligence and Image Processing
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008
Qualifications
- PhD in Computer Systems Engineering (Uni of South Australia)
Professional memberships and associations
- Please visit Google Scholar Citations of my publications.
- Please visit my QUT ePrints or DBLP page in computer science bibliography for access to my publications.
- Please visit ‘Experience’ page regarding my current research topics and projects for study/collaboration.
Teaching
"Teaching is the highest level of learning". I am passionate about teaching. I believe high quality teaching is underpinned by solid and in depth knowledge and wisdom, and driven by dedication and passion to engage and to inspire.
Teaching Disciplines: Information Systems; Business Process Management; Service Science
Academic Program Coordination: JIT-QUT Bachelor of IT Program (since June 2017)
Course Coordination: Master of Business Process Management (07/2018 - 07/2019)
Subject Coordination & Lecturing:
- IFN667 Enterprise IoT Systems (new subject from 2020)
- IFN515 Fundamentals of Business Process Management (2015-2019)
- IFN651 Lean Six Sigma (2015-2019)
- INN610 Case Studies in Business Process Management (2010-2014)
Subject Co-lecturing:
- IAB201 Modelling Techniques for Information Systems (2021)
- INB/N324 Business Process Analytics (2012-2014)
- INB/N210 Databases (2009-2014)
Subject Guest-lecturing:
- IAB201 Modelling Information Systems - Guest lecture on Object-oriented Modelling (2014-2016)
- INN701 Advanced Research Topics - Guest lectures on Petri nets and Object Role Modelling as part of a one-day module on Introduction to Formal Methods (2009-2014)
Project Co-teaching / Supervision:
- IFN703 Advanced Project (2021)
- IFN704 Advanced Project 2 (2021)
- IAB398/399 Undergraduate student capstone project supervision (2019-2020)
- IFN701/702 Postgraduate student project supervision - incl: CEED & WIL project supervision (since 2015)
- IFN690/691/693 Postgraduate student project supervision (prior to 2015)
- INB300/302 Undergraduate student project supervision (prior to 2015)
- CEED project supervision (prior to 2015)
Invited Subject (Co-)Teaching (external to QUT):
- Business Process Automation: An undergraduate subject at Sun Yat-sen University (2013-2015)
Research Supervision:
QUT Internal (Access to the theses of my research graduates can be found on 'Supervision' page)
- Jing Yang (PhD student; principal supervisor; co-supervising with Prof Arthur ter Hofstede, Prof Wil van der Aalst)
- Chathurika Wickramage (PhD student; co-supervising with Prof Colin Fidge)
- Shilpa Kochar (MPhil student; co-supervising with Dr Jason Watson)
- Fuguo Wei (PhD graduate in 2016; co-supervised with Prof Alistair Barros)
- Suriadi Suriadi (PhD graduate in 2010; co-supervised with Dr Ernest Foo)
- Kenneth Wang (PhD graduate in 2008; co-supervised with Prof Marlon Dumas)
- Srimanth Lingamaneni (Master by Research graduate in 2010; co-supervised with Prof Lin Ma and Prof Prasad Yarlagadda)
External to QUT (I provide guidance and mentoring to the following research students outside QUT, though I am not officially their supervisor on administrative document)
- Jing Yang (Master by Research graduate in 2019; Sun Yat-sen University, China)
- Amin Jalali (PhD graduate in 2016; Stockholm University, Sweden)
- Zhaoxia Wang (PhD graduate in 2012; Tsinghua University, China)
(Information is up to date as on 08/11/2019)
Experience
I am inspired and strongly motivated by research-driven innovation. I enjoy teamwork and welcome collaboration with those who share common research value and interests with me. I understand the importance of industry-informed research and enjoy working with industry partners who respect and value research and researchers. Based on my substantial research experience in the past 14 years, I believe that a true researcher is genuine, passionate and dedicated, conducts deep thinking and deep work, and has an ongoing interest in pursuing new ideas and knowledge creation. I admire true research leaders not in how big a team they lead but in how they lead their team. I believe a true research leader is a true researcher who is self-leading (with strong personal commitment) and leading others (by being able to motivate, inspire, engage, and instil a positive attitude into the team). True research leaders do not only drive an initiative but also they deep 'dive' with their team in tackling research challenges. Below is a list of my current major research initiatives. More details of the research topics (including background, overview, and some earlier thoughts) can be found on my project pages on QUT research topics for Science and Engineering students. If you are interested in studying or collaborating in the context of any of these topics from either scientific or practical perspective, please feel free to contact me.
Guided Process Analytics (QUT project page)
- New methods and techniques for querying process event logs to retrieve, aggregate, and/or infer relevant and reliable data for process analysis
- A 'tool box' of data-driven process analysis capabilities (in the forms of e.g., methods, algorithms, techniques) motivated by and to inform actionable recommendations for process improvement
- Systematic approach for generating log requirements to guide data curation for continuous (and automated) process analytics
My past and recent publications related to or leading into this initiative:
- S. Suriadi, C. Ouyang, W.M.P. van der Aalst, A.H.M. ter Hofstede. Root Cause Analysis with Enriched Process Logs. In the 8th International Workshop on Business Process Intelligence (BPI 2012) as part of the Proceedings of Business Process Management Workshops 2012 (revised papers): 174-186
- S. Suriadi, C. Ouyang, W.M.P. van der Aalst, A.H.M. ter Hofstede. Event interval analysis: Why do processes take time? Decision Support Systems 79: 77-98 (2015)
- A. Polyvyanyy, C. Ouyang, A. Barros, W.M.P. van der Aalst. Process querying: Enabling business intelligence through query-based process analytics. Decision Support Systems 100: 41-56 (2017)
- R. Andrews, S. Suriadi, C. Ouyang, E. Poppe. Towards Event Log Querying for Data Quality - Let's Start with Detecting Log Imperfections. In Proceedings of the International Conference on Cooperative Information Systems (CoopIS and as part of OTM Conferences 2018): 116-134
- W. Chathurika, C. Fidge, C. Ouyang, T. Sahama. Generating Log Requirements for Checking Conformance against Healthcare Standards using Workflow Modelling. In the 12th Australasian Conference on Health Informatics and Knowledge (HIKM 2019), 29 - 31 January 2019, Sydney, Australia. (In Press)
(Process-oriented) Organisational Mining (QUT project page)
- New/improved methods and algorithms for organisational model mining built upon suitable data mining techniques
- Novel approach and models for discovering, reasoning, and analysing (intra-)organisational and inter-organisational networks by leveraging existing social network analysis capabilities
- New tools and visualisation of the discovered organisational networks
- Knowledge discovery from process event logs for organisational improvement informed by management science
My recent publication under this initiative:
- J. Yang, C. Ouyang, M. Pan, Y. Yu, A.H.M. ter Hofstede. Finding the "Liberos": Discover Organizational Models with Overlaps. In Proceedings of the 16th International Conference on Business Process Management (BPM 2018): 339-355
BPM in the Cloud (QUT project page)
- Design of generic and scalable system architecture
- Architectural solution built on and empowered by microservices
- Performance evaluation framework for Cloud-based BPMS
- Workload balancing strategies to support (stateful) process execution
- SLA, pricing model, and computing cost for BPM-as-a-Service (BPMaaS)
- System reliability issues such as data management, access control and security
My recent publications under this initiative:
- C. Ouyang, M. Adams, A.H.M. ter Hofstede, Y. Yu. Towards the Design of a Scalable Business Process Management System Architecture in the Cloud. In Proceedings of the 37th International Conference on Conceptual Modeling (ER 2018): 334-348
- M. Adams, C. Ouyang, A.H.M. ter Hofstede, Y. Yu. Design and Performance Analysis of Load Balancing Strategies for Cloud-Based Business Process Management Systems. In Proceedings of the International Conference on Cooperative Information Systems (CoopIS and as part of OTM Conferences 2018): 390-406
(Information is up to date as on 01/12/2018)
Publications
- Wickramanayake, B., Ouyang, C., Xu, Y. & Pinto Moreira, C. (2023). Generating multi-level explanations for process outcome predictions. Engineering Applications of Artificial Intelligence, 125. https://eprints.qut.edu.au/241377
- Velmurugan, M., Ouyang, C., Sindhgatta, R. & Pinto Moreira, C. (2023). Through the looking glass: Evaluating post hoc explanations using transparent models. International Journal of Data Science and Analytics. https://eprints.qut.edu.au/243164
- Yang, J., Ouyang, C., van der Aalst, W., ter Hofstede, A. & Yu, Y. (2022). OrdinoR: A framework for discovering, evaluating, and analyzing organizational models using event logs. Decision Support Systems, 158. https://eprints.qut.edu.au/228693
- Wickramanayake, B., He, Z., Ouyang, C., Pinto Moreira, C., Xu, Y. & Sindhgatta, R. (2022). Building interpretable models for business process prediction using shared and specialised attention mechanisms. Knowledge-Based Systems, 248. https://eprints.qut.edu.au/229607
- Pika, A., Ouyang, C. & ter Hofstede, A. (2022). Configurable Batch-Processing Discovery from Event Logs. ACM Transactions on Management Information Systems, 13(3). https://eprints.qut.edu.au/213735
- Chou, Y., Pinto Moreira, C., Bruza, P., Ouyang, C. & Jorge, J. (2022). Counterfactuals and causability in explainable artificial intelligence: Theory, algorithms, and applications. Information Fusion, 81, 59–83. https://eprints.qut.edu.au/225948
- Yang, J., Ouyang, C., Dik, G., Corry, P. & ter Hofstede, A. (2022). Crop Harvest Forecast via Agronomy-informed Process Modelling and Predictive Monitoring. Advanced Information Systems Engineering: 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6–10, 2022, Proceedings, 201–217. https://eprints.qut.edu.au/229877
- Ouyang, C., Adams, M., ter Hofstede, A. & Yu, Y. (2021). Design and Realisation of Scalable Business Process Management Systems for Deployment in the Cloud. ACM Transactions on Management Information Systems, 12(4). https://eprints.qut.edu.au/212227
- Moreira, C., Chou, Y., Velmurugan, M., Ouyang, C., Sindhgatta, R. & Bruza, P. (2021). LINDA-BN: An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models. Decision Support Systems, 150. https://eprints.qut.edu.au/211178
- Velmurugan, M., Ouyang, C., Pinto Moreira, C. & Sindhgatta, R. (2021). Evaluating Stability of Post-hoc Explanations for Business Process Predictions. Service-Oriented Computing: 19th International Conference, ICSOC 2021, Virtual Event, November 22–25, 2021, Proceedings, 49–64. https://eprints.qut.edu.au/214090
QUT ePrints
For more publications by Chun, explore their research in QUT ePrints (our digital repository).
Selected research projects
- Title
- Re-Engineering Enterprise Systems for Microservices in the Cloud
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP190100314
- Start year
- 2019
- 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
- Collaboration with Beijing Jiaotong University to build Australia-China research-industry collaboration in service and process innovation
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- ACSRF01226
- Start year
- 2012
- Keywords
- Business Process Management; Service Engineering
- 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
- 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
Projects listed above are funded by Australian Competitive Grants. Projects funded from other sources are not listed due to confidentiality agreements.
Supervision
Current supervisions
- Evaluating Post Hoc Explanations using Tabular Data and for Predictive Process Analytics: A Functionally-Grounded Perspective
PhD, Principal Supervisor
Other supervisors: Dr Renuka Sindhgatta Rajan, Adjunct Associate Professor Catarina Pinto Moreira, Associate Professor Yue Xu - Explaining Deep Learning-based Process Predictions
PhD, Principal Supervisor
Other supervisors: Associate Professor Yue Xu, Adjunct Associate Professor Catarina Pinto Moreira - Interpretable Human-Centred Multimodal Learning Framework
PhD, Associate Supervisor
Other supervisors: Adjunct Associate Professor Catarina Pinto Moreira, Professor Margot Brereton - Building Robust Predictive Systems for Structured Data
PhD, Principal Supervisor
Other supervisors: Professor Alistair Barros, Adjunct Associate Professor Catarina Pinto Moreira - Context-aware Process Analytics using IoT Data
PhD, Principal Supervisor
Other supervisors: Professor Arthur ter Hofstede
Completed supervisions (Doctorate)
- Discovering organizational models from event logs for workforce analytics (2023)
- Information Accountability in Health Information Systems Using Process Analytics (2020)
- On the Analysis and Refactoring of Service Interfaces for Improving Service Integration Efficiency (2016)
- Strengthening and Formally Verifying Privacy in Identity Management Systems (2010)
- Interface Adaptation for Conversational Services (2008)