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PhD in Computer Systems Engineering (Uni of South Australia)
I am a co-founder and leader of the “eXplainable Analytics for Machine Intelligence” team (XAMI Lab), driven by a vision to foster fairness, transparency, and trust in data-centric AI systems. I am co-leading the Responsible Data Science & AI Program in the Centre for Data Science. I am the Academic Lead in Higher Degree Research in the school, providing leadership in training and mentoring PhD/master research students. I am the program leader of Bachelor of IT joint teaching program between QUT and Jinling Institute of Technology.
I am a well-established researcher and my work contributes to the advancement of data analytical capabilities by developing new methods and techniques underpinned by data mining. I am passionate in applying data science to address real-world challenges, and my recent work focus on developing explainable analytics for machine learning. I have published over 100 peer-reviewed research papers in international journals and conference proceedings (refer to Publications section and my Google Scholar page). I have been awarded numerous research grants, including five Category 1 Australian Competitive Grants (refer to Research projects section), two major research-industry projects funded by food agility CRC, three joint grants between QUT and Sun Yat-Sen University, etc.
I am dedicated to fostering the development and success of research students, and actively seeking prospective PhD, master, and honours students interested in exploring research topics such as explainable AI, workforce analytics, IoT computing, process mining, robotic process automation, and trustworthy intelligent systems. Please refer to the Supervision section for detailed information on specific research projects under my supervision.
Additional information
- 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
- Ouyang, C., Sindhgatta, R., Pinto Moreira, C. & Velmurugan, M. (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
- 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
- Context-Aware Anomaly Detection in Time Series Data
PhD, Principal Supervisor
Other supervisors: Associate Professor Sara Khalifa - Building Robust Predictive Systems for Structured Data
PhD, Principal Supervisor
Other supervisors: Professor Alistair Barros - Context-aware Process Analytics using IoT Data
PhD, Principal Supervisor
Other supervisors: Professor Arthur ter Hofstede - Deep Learning Explainability for Predictive Process Analytics via Intrinsic Techniques
PhD, Principal Supervisor
Other supervisors: Associate Professor Yue Xu - Developing Metrics, Analytics, and Guidelines for Successful Business Transformation; process intelligence
PhD, Principal Supervisor
Other supervisors: Dr Roy Yang - Foundations of Modelling Robotic Process Automation
PhD, Principal Supervisor
Other supervisors: Professor Arthur ter Hofstede, Dr Rehan Syed, Dr Roy Yang - Interpretable Human-Centred Multimodal Learning Framework
PhD, Associate Supervisor
Other supervisors: Adjunct Associate Professor Catarina Pinto Moreira, Professor Margot Brereton - Clinical Investigation of Early GHOA Using Integrated Automatic Image Segmentation Method Followed by DL-based Computational Analysis Pipeline
PhD, Associate Supervisor
Other supervisors: Professor YuanTong Gu
- Evaluating post hoc explanations using tabular data: A functionally-grounded perspective (2024)
- 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)
- Counterfactuals in explainable artificial intelligence: Theory, algorithms, and applications (2024)
- Developing a conceptual framework towards data-driven business process redesign (2024)
- Network Ties and Their Effect on Employee Collaboration in Enterprise Social Networks (2021)
- Modelling and Execution of Asset Management Process via Workflow Automation (2010)