Dr Robert Andrews
Faculty of Science,
School of Information Systems
Biography
Robert Andrews first joined QUT in 1990. During the period 1990-2001 he worked as an academic in the School of Information Systems, teaching mainly in relational database, and researching in the area of machine learning and explainable neural networks. He gained his PhD in this area in 2003 and spent the next 13 years as an IT consultant working in a variety of industry sectors including accounting, finance, and manufacturing. Robert re-joined the School of Information Systems' Business Process Management group in 2016 as a research fellow working on applying process mining techniques in the healthcare and insurance sectors, and in wildlife hazard management for Brisbane Airport Corporation. In 2019, Robert took a role as senior lecturer teaching information systems modelling techniques. He is currently a senior research fellow working with the BPM group and the Motor Accident Insurance Commission applying process mining techniques in the healthcare sector - specifically pre-hospital retrieval and transport, patient journeys and outcomes following major trauma. This project aims to improve and standardise processes and information exchange at points of articulation between the emergency services and hospital system processes. Robert is also working with the Queensland Critical Care Network setting up a statewide ICU registry for blood-borne infections, and with QUT's Centre for Data Science modelling hospital capacity and case mix planning. Robert has a long-standing interest in process-data quality. He has collaborated with researchers around the world in this area, resulting in several highly cited publications, and has established the process data quality website (processdataquality.com) as a resource for other researchers interested in this emerging research area.Personal details
Positions
- Senior Research Fellow
Faculty of Science,
School of Information Systems
Keywords
Process mining, Data mining, Business intelligence
Research field
Information systems, Strategy, management and organisational behaviour
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020
Qualifications
- PhD (Queensland University of Technology)
- MInfoTech (Queensland University of Technology)
- GDComComp (Queensland University of Technology)
- PHD (Queensland University of Technology)
- DipT (Kelvin Grove C.A.E)
Experience
2020 - present Research Fellow (School of Information Systems) Application of process mining and data science techniques in
- healthcare (Queensland Ambulance Service, Retrieval Services Queensland, Queensland Health, Princess Alexandra Hospital, Queensland Children's Hospital, Mater Hospital)
- blood-borne infection statewide ICU registry
- hospital capacity modelling and case mix planning
2019 - Senior Lecturer - QUT (School of Information Systems)
- teaching - Modelling Techniques for Information Systems
- research - process data quality
2016 - 2018 Research Fellow (School of Information Systems) Application of process mining and data science techniques in
- healthcare (St Andrews' War Memorial Hospital, Princess Alexandra Hospital, Queensland Ambulance Service, Retrieval Services Queensland, Queensland Health)
- CTP insurance (Motor Accident Insurance Commission)
- wildlife hazard risk management (Brisbane Airport Corporation)
- process data quality
2001 - 2016 - IT Consultant (Access Management Consultants, MYP Corporation)
- System analysis & design
- Requirements specifications
- Tender management
- ERP System/supplier selection & implementation
- Forensic computing
- Data mining – intelligent systems
- Software system verification
- Systems audit
- Web development
- Application development (including mobile applications)
1991 - 2001 - Lecturer - QUT (School of Information Systems)
- teaching - relational database, ABAP programming, office automation
- research - artificial neural networks and rule-based explanation mechanisms
1990 - COBOL Programmer - SciTech (State Government Computing)
Publications
- van Dun, C., Wynn, M., Kratsch, W., Roglinger, M., ter Hofstede, A. & Andrews, R. (2020). Quality-informed semi-automated event log generation for process mining. Decision Support Systems, 132. https://eprints.qut.edu.au/180260
- Emamjome, F., Andrews, R. & ter Hofstede, A. (2019). A case study lens on process mining in practice. On the Move to Meaningful Internet Systems: OTM 2019 Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Proceedings (Lecture Notes in Computer Science, Volume 11877), 127–145. https://eprints.qut.edu.au/133712
- Andrews, R., Wynn, M., ter Hofstede, A., Xu, J., Horton, K., Taylor, P. & Plunkett-Cole, S. (2018). Exposing impediments to insurance claims processing: Compulsory third party insurance in Queensland. In J. Mendling & J. vom Brocke (Eds.), Business process management cases: Digital innovation and business transformation in practice (Management for Professionals) (pp. 275–290). Springer. https://eprints.qut.edu.au/104812
- Andrews, R., Suriadi, S., Wynn, M. & ter Hofstede, A. (2018). Healthcare process analysis. In C. Combi, G. Pozzi & P. Veltri (Eds.), Process modeling and management for healthcare (Chapman and Hall/CRC Healthcare Informatics Series) (pp. 165–194). CRC Press. https://eprints.qut.edu.au/104813
- Andrews, R., Suriadi, S., Wynn, M., ter Hofstede, A. & Rothwell, S. (2018). Improving patient flows at St. Andrew's War Memorial Hospital's emergency department through process mining. In J. Mendling & J. vom Brocke (Eds.), Business process management cases: Digital innovation and business transformation in practice (Management for Professionals) (pp. 311–333). Springer. https://eprints.qut.edu.au/104811
- Andrews, R. & Wynn, M. (2017). Shelf time analysis in CTP insurance claims processing. Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2017 Workshops, MLSDA, BDM, DM-BPM, Revised Selected Papers (Lecture Notes in Artificial Intelligence, Volume 10526), 151–162. https://eprints.qut.edu.au/104246
- Andrews, R. & Geva, S. (2002). Rule Extraction from Local Cluster Neural Nets. Neurocomputing, 47, 1–20. https://eprints.qut.edu.au/9872
- Andrews, R., Diederich, J. & Tickle, A. (1995). Survey And Critique Of Techniques For Extracting Rules From Trained Artifical Neural Networks. Knowledge-Based Systems, 373–390.
QUT ePrints
For more publications by Robert, explore their research in QUT ePrints (our digital repository).