Selected Publications
- Pathiraja, S., Reich, S., Stannat, W. (2021) McKean-Vlasov SDEs in non-linear filtering, SIAM Journal on Control and Optimization, 59(6), DOI: 0.1137/20M1355197.
- Pathiraja, S., Stannat, W. (2021) Analysis of the Feedback Particle Filter with diffusion map based approximation of the gain, Foundations of Data Science, 3(3), DOI: 10.3934/fods.2021023.
- Pathiraja, S. (2022) L2 Convergence of Smooth approximations of stochastic differential equations with unbounded coefficients, Stochastic Analysis and Applications (accepted).
- Pathiraja, S., Marshall, L., Sharma, A. and Moradkhani, H. (2016) Hydrologic modeling in dynamic catchments: a data assimilation approach, Water Resources Research, 52, pp. 3350-3372. DOI: 10.1002/2015WR017192.
- Pathiraja, S., Marshall, L., Sharma, A. and Moradkhani, H. (2016) Detecting non-stationary hydrologic model parameters in a paired catchment system using data assimilation, Advances in Water Resources. 94, pp. 103-119. DOI: 10.1016/j.advwatres.2016.04.021.
- Pathiraja, S., Moradkhani, H., Marshall, L., Sharma, A. and Geenens, G. (2018) Data-driven model uncertainty estimation in hydrologic data assimilation, Water Resources Research, 54(2), pp. 1252-1280. DOI: 10.1002/2018WR022627.
YAS Project
- Environmental Knowledge of Disastrous Water in Urban Europe (with Luisa Cortesi and Corinna Köpke)
Other projects & third-party funding
- Eva Mayr Stihl Foundation Seed Funding “Natural Hazards and Resilient Regions” (30,000 EUR)
- UNSW Faculty Research Grant for project “Bayesian Deep Learning for Climate Extremes” ($15,000 AUD)
- CSIRO Next Generation Graduate Program Funding “Sports Data Science and AI” ($2.3 Million AUD)