Doctor of Philosophy (Queensland University of Technology), Master of Enginering Science (Computer and Comm Engineering) (Queensland University of Technology), Bachelor of Engineering (Electrical and Computer Engineering (Queensland University of Technology)
I am an industry research fellow in our strategic partnership between the Centre for Data Science (CDS) and AIS/QAS, and a senior lecturer in the School of Mathematical Sciences. I also lead the sports systems domain in CDS. Starting life in aerospace engineering (Artificial Intelligence (AI) for unmanned aircraft), I have worked in projects across defence, airports, marine science and sports industries. My focus is on developing and applying statistical and machine learning models in collaboration with domain experts and end-users to solve complex systems problems. I have extensive experience in methods including Bayesian statistics, state space modelling, Dynamic Bayesian Networks, simulation modelling and queuing models.
Some highlight publications:
P. P.-Y. Wu et al., "Timing anthropogenic stressors to mitigate their impact on marine ecosystem resilience," Nature communications, vol. 8, no. 1, p. 1263, 2017.
P. P. Y. Wu, M. Julian Caley, G. A. Kendrick, K. McMahon, and K. Mengersen, "Dynamic Bayesian network inferencing for non‐homogeneous complex systems," Journal of the Royal Statistical Society: Series C (Applied Statistics), vol. 67, no. 2, pp. 417-434, 2018.
Wu, P. P.-Y., Babaei, T., O’Shea, M., Mengersen, K., Drovandi, C., McGibbon, K. E., Pyne, D. B., Mitchell, L. J. G., Osborne, M. A. (2021). Predicting performance in 4 x 200-m freestyle swimming relay events. PloS one, 16(7), p e0254538.
P. P.-Y. Wu, N. Sterkenburg, K. Everett, D. W. Chapman, N. White, and K. Mengersen, "Predicting fatigue using countermovement jump force-time signatures: PCA can distinguish neuromuscular versus metabolic fatigue," PloS one, vol. 14, no. 7, p. e0219295, 2019.
P. P.-Y. Wu, D. Campbell, and T. Merz, "Multi-objective four-dimensional vehicle motion planning in large dynamic environments," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 41, no. 3, pp. 621-634, 2010.
“Some of the insights gained from several key areas of targeted investigation have contributed to Australia winning 4 out of 7 Gold Medals at the 2019 Swimming World Championships” (Mark Osborne, General Manager, SAL).
“Paul and his team have provided a level of data analytics expertise that has changed our interpretation of subsequent injuries in elite Australian football. His work on Bayesian survival modelling has become instrumental in the club’s internal decision-making processes about returning injured players to the competitive arena and provides a great example of how this field can be utilised in elite sport”. (Jordan Stares, Strength and Conditioning Coach, West Coast Eagles).
“I can attest to Paul’s extensive contributions to teaching, research and industry collaborations. He has been very proactive in seeking, securing and executing successful industry partnerships.” (Prof. David Pyne, AIS, UC)
I have worked on over 25 collaborative projects with a broad array of industry, government and academic collaborators in sports data science. Collaborators include: Australian Institute of Sport (AIS), Queensland Academy of Sport (QAS), Victoria Institute of Sport (VIS), Western Australia Institute of Sport (WAIS), Swimming Australia, Tennis Australia, Triathlon Australia, Paddle Australia, West Coast Eagles, Cricket Australia/Queensland, and more.