activity
19992025
most citedQuantitative study of molecular N_2 trapped in disordered GaN:O films

37 citations · 170 across the 18 of their papers we have counts for

collaborators

18 papers

physics.optics2025

Density-encoded line integral convolution: polarisation optical axis tractography using centroidal Voronoi tessellation

Darven Murali Tharan, Marco Bonesi, Daniel Everett +4

Visualising complex polarimetry optical axis fields is challenging. We introduce density-encoded line integral convolution (DELIC), a novel approach that builds on the classic line…

physics.optics2025

Depth-resolved polarisation sensitive optical coherence tomography reveals the complex microanatomical response of cartilage to compression

Darven Murali Tharan, Marco Bonesi, Daniel Everett +5

Conventional methods for analysing cartilage microstructure under mechanical loading are largely destructive. In this work, we evaluate the efficacy of using depth-resolved polaris…

cs.CV2025★ 3 cited

Foundation Models -- A Panacea for Artificial Intelligence in Pathology?

Nita Mulliqi, Anders Blilie, Xiaoyi Ji +28

The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole slide images (WSIs). Recently, fo…

physics.geo-ph2024

A machine learning algorithm for predicting naturalized flow duration curves at human influenced sites and multiple catchment scales

Michael J. Friedel, Dave Stewart, Xiao Feng Lu +3

Regional flow duration curves (FDCs) often reflect streamflow influenced by human activities. We propose a new machine learning algorithm to predict naturalized FDCs at human influ…

physics.geo-ph2023★ 2 cited

A simple stacked ensemble machine learning model to predict naturalized catchment hydrology and allocation status

Michael J. Friedel, Dave Stewart, Xiao Feng Lu +3

New Zealand legislation requires that Regional Councils set limits for water resource usage to manage the effects of abstractions in over-allocated catchments. We propose a simple…

eess.SY2022

Monitoring and Detection of Low-current High-Impedance Faults in Distribution Networks

Anwarul Islam Sifat, Fiona J. Stevens McFadden, Ramesh Rayudu +1

Faults in electricity distribution networks have the potential to ignite fires, cause electrocution, and damage the system itself. High current Low Impedance Faults (LIF) are typic…