| Issue Date | Title | Author(s) |
| 2020-10-01 | Fast multi-resolution segmentation for nonstationary Hawkes process using cumulants | Zhou, F; Li, Z; Fan, X; Wang, Y; Sowmya, A; Chen, F |
| 2020-06-05 | Utilizing machine learning to prevent water main breaks by understanding pipeline failure drivers | Weeraddana, D; Liang, B; Li, Z; Wang, Y; Chen, F; Bonazzi, L; Phillips, D; Saxena, N |
| 2020-12-01 | Efficient inference for nonparametric hawkes processes using auxiliary latent variables | Zhou, F; Li, Z; Fan, X; Wang, Y; Sowmya, A; Chen, F |
| 2023-10-31 | Optimizing water quality with data analytics and machine learning | Liang, B; Li, Z; Tian, H; Liang, S; Wang, Y; Chen, F |
| 2022-12-02 | Machine Learning for Efficient Water Infrastructure Management | Li, Z; Liang, B; Wang, Y |
| 2021-01-01 | A Multi-task Kernel Learning Algorithm for Survival Analysis | Meng, Z; Xu, J; Li, Z; Wang, Y; Chen, F; Wang, Z; Karlapalem, K; Cheng, H; Ramakrishnan, N; Agrawal, RK; Reddy, PK; Srivastava, J; Chakraborty, T |
| 2016-01-01 | Robust Bayesian non-parametric dictionary learning with heterogeneous Gaussian noise | Wang, Y; Li, B; Wang, Y; Chen, F; Zhang, B; Li, Z |
| 2021-02-25 | Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis | Weeraddana, D; MallawaArachchi, S; Warnakula, T; Li, Z; Wang, Y |
| 2018 | SUCCESS IN DATA ANALYTICS - SYDNEY WATER AND DATA61 COLLABORATION | Vitanage, D; Doolan, C; Maunsell, L; Cameron, B; Wang, Y; Li, Z |
| 2016-01-01 | Making machine learning useable by revealing internal states update - a transparent approach | Chen, F; Sun, J; Wang, Y; Khawaja, MA; Li, Z; Zhou, J |
