| A framework for automated anomaly detection in high frequency water-quality data from in situ sensors C Leigh, O Alsibai, RJ Hyndman, S Kandanaarachchi, OC King, ... Science of The Total Environment 664, 885-898, 2019 | 103 | 2019 |
| On normalization and algorithm selection for unsupervised outlier detection S Kandanaarachchi, MA Muñoz, RJ Hyndman, K Smith-Miles Data Mining and Knowledge Discovery 34 (2), 309-354, 2020 | 75 | 2020 |
| Anomaly detection in streaming nonstationary temporal data PD Talagala, RJ Hyndman, K Smith-Miles, S Kandanaarachchi, ... Journal of Computational and Graphical Statistics 29 (1), 13-27, 2020 | 70 | 2020 |
| Predicting sediment and nutrient concentrations from high-frequency water-quality data C Leigh, S Kandanaarachchi, JM McGree, RJ Hyndman, O Alsibai, ... PloS one 14 (8), e0215503, 2019 | 46 | 2019 |
| Predicting sediment and nutrient concentrations from high-frequency water-quality data C Leigh, S Kandanaarachchi, JM McGree, RJ Hyndman, O Alsibai, ... PloS one 14 (8), 2019 | 43 | 2019 |
| Early detection of vegetation ignition due to powerline faults S Kandanaarachchi, N Anantharama, MA Munoz IEEE Transactions on Power Delivery 36 (3), 1324-1334, 2020 | 40 | 2020 |
| Machine learning methods for predicting the outcome of hypervelocity impact events S Ryan, S Thaler, S Kandanaarachchi Expert Systems with Applications 45, 23-39, 2016 | 37 | 2016 |
| Convergence of axially symmetric volume-preserving mean curvature flow M Athanassenas, S Kandanaarachchi Pacific Journal of Mathematics 259 (1), 41-54, 2012 | 25 | 2012 |
| Singularities of Axially Symmetric Volume Preserving Mean Curvature Flow M Athanassenas, S Kandanaarachchi arXiv preprint arXiv:1203.5671, 2012 | 25* | 2012 |
| Unsupervised anomaly detection ensembles using item response theory S Kandanaarachchi Information Sciences 587, 142-163, 2022 | 22 | 2022 |
| Honeyboost: Boosting honeypot performance with data fusion and anomaly detection S Kandanaarachchi, H Ochiai, A Rao Expert Systems with Applications 201, 117073, 2022 | 14 | 2022 |
| Dimension reduction for outlier detection using DOBIN S Kandanaarachchi, RJ Hyndman Journal of Computational and Graphical Statistics, 1-16, 2020 | 13 | 2020 |
| Support vector machines for characterising Whipple shield performance S Ryan, S Kandanaarachchi, K Smith-Miles Procedia Engineering 103, 522-529, 2015 | 12 | 2015 |
| The application of machine learning in micrometeoroid and orbital debris impact protection and risk assessment for spacecraft S Ryan, NM Sushma, H Le, AVA Kumar, J Berk, TM Nguyen, S Rana, ... International Journal of Impact Engineering 181, 104727, 2023 | 8 | 2023 |
| Instance space analysis for unsupervised outlier detection S Kandanaarachchi, MA Munoz, K Smith-Miles Evaluation and Experimental Design in Data Mining and Machine Learning 2019, 2019 | 8 | 2019 |
| Leave-one-out kernel density estimates for outlier detection S Kandanaarachchi, RJ Hyndman Journal of Computational and Graphical Statistics, 2021 | 7 | 2021 |
| Datasets for outlier detection S Kandanaarachchi, MM Acosta, K Smith-Miles, R Hyndman URL: https://monash. figshare. com/articles/Datasets_12338_zip/7705127/4, 2019 | 6 | 2019 |
| Short‐term prediction of stream turbidity using surrogate data and a meta‐model approach: A case study B Rele, C Hogan, S Kandanaarachchi, C Leigh Hydrological Processes 37 (4), e14857, 2023 | 5 | 2023 |
| Comprehensive Algorithm Portfolio Evaluation using Item Response Theory S Kandanaarachchi, K Smith-Miles Journal of Machine Learning Research, 2023 | 4 | 2023 |
| Axially symmetric volume preserving mean curvature flow SP Kandanaarachchi Monash University, 2011 | 4 | 2011 |
Rob J HyndmanProfessor of Statistics, Monash UniversityEmail verificata su monash.edu