- Associate Investigators
- Paul Wu
Dr Paul Wu
Research Fellow, Associate Investigator
Queensland University of Technology
I am an engineer turned statistician who gets to work on exciting projects across many disciplines with really cool people. Last year, I was awarded a visiting fellow scholarship to ECU.
Some of the work I am currently involved in include:
- Predicting and understanding ecological windows to minimise the impact of human activities on marine ecosystems such as seagrass. An array of methods including non-homogeneous state space models (DBNs), Bayesian multilevel models and other methods such as functional PCA are developed for this. This work is also being used to inform activities such as the Great Barrier Reef integrated monitoring program. It involves a broad collaboration with AIMS, WAMSI, ECU, UWA, JCU, regulators in Qld and WA, and international collaborators.
- Benchmarking of social services to support managers and policy makers in improving performance.
- A program of research in sports including predictive modelling of fatigue using PCA and the countermovement jump, analysis of posture control, and addressing the challenges of longitudinal data with wearable technologies. This is a collaboration with the AIS.
- Predicting and supporting the management of queues and passenger flows in airports through development of inhomogeneous queuing models and Approximate Bayesian Computation. This is a linkage project with Brisbane Airport, Gold Coast Airport, Border Force and ISS.
- Healthy waterways project, supporting the design of policy and advice for safe use of public swim sites such as beaches, estuaries and lakes. This is for city councils in the region south-east Queensland region.
Bayesian statistical modelling
Dynamic Bayesian Networks
multi-criteria decision making
Non-homogeneous state space models
search and optimisation algorithms
PhD, Avionics, Queensland University of Technology
Invited talks, refereed proceedings and other conference outputs
Ebert, A., Wu P., Mengersen KL., & Ruggeri F. (2018). A Review of Distances on Functional Datasets for Likelihood-Free Inference. Joint International Society for Clinical Biostatistics and Australian Statistical Conference 2018.
Ebert, A., Wu P., Mengersen KL., & Ruggeri F. (2017). Efficient simulation of complex queueing systems with the R package queuecomputer. French R meeting.
Ebert, A., Wu P., Dutta R., Mengersen KL., Ruggeri F., Mira A., et al. (2017). Approximate Bayesian Computation for Dynamic Queueing Networks. 5th Symposium on Games and Decisions in Reliability and Risk.
Cook, A., Wu P., & Mengersen KL. (2015). Machine learning and visual analytics for consulting business decision support. 2015 Big Data Visual Analytics (BDVA). doi: 10.1109/BDVA.2015.7314299
Wu, P., M. Caley J., Kendrick G. A., McMahon K., & Mengersen KL. (2018). Dynamic Bayesian network inferencing for non-homogeneous complex systems. Journal of the Royal Statistical Society: Series C (Applied Statistics). 67(2), 417-434. doi: 10.1111/rssc.12228
Wu, P., McMahon K., Rasheed M. A., Kendrick G. A., York P. H., Chartrand K., et al. (2018). Managing seagrass resilience under cumulative dredging affecting light: Predicting risk using dynamic Bayesian networks. Journal of Applied Ecology. 55(3), 1339-1350. doi: 10.1111/1365-2664.13037
Colin, B., Clifford S., Wu P., Rathmanner S., & Mengersen KL. (2017). Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision-Making. Open Journal of Statistics. 07(05), 859 - 875. doi: 10.4236/ojs.2017.75061
Fraser, M. W., Short J., Kendrick G., McLean D., Keesing J., Byrne M., et al. (2017). Effects of dredging on critical ecological processes for marine invertebrates, seagrasses and macroalgae, and the potential for management with environmental windows using Western Australia as a case study. Ecological Indicators. 78, 229 - 242. doi: 10.1016/j.ecolind.2017.03.026
Wu, P., Mengersen KL., McMahon K., Kendrick G. A., Chartrand K., York P. H., et al. (2017). Timing anthropogenic stressors to mitigate their impact on marine ecosystem resilience. Nature Communications. 8(1), doi: 10.1038/s41467-017-01306-9
Pitchforth, J., Wu P., Fookes C., & Mengersen KL. (2015). Processing passengers efficiently: An analysis of airport processing times for international passengers. Journal of Air Transport Management. 49, 35-45. doi: 10.1016/j.jairtraman.2015.06.016
Wu, P., Fookes C., Pitchforth J., & Mengersen KL. (2015). A framework for model integration and holistic modelling of socio-technical systems. Decision Support Systems. 71, 14-27. doi: 10.1016/j.dss.2015.01.006
Wu, P., Pitchforth J., & Mengersen KL. (2014). A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling. Transportation Research Part C: Emerging Technologies. 46, 247-260. doi: 10.1016/j.trc.2014.05.005
Publicly available softwares
Technical reports and unrefereed outputs
Ebert, A., Wu P., Mengersen KL., & Ruggeri F. (2017). Computationally Efficient Simulation of Queues: The R Package queuecomputer. arXiv.
McBain, M., Fitzpatrick B., Colin B., Gough P., Wu P., & Mengersen KL. (2016). Dashboard project for Australian Agricutural Company.
61 7 3138 9828