Rate My Professor Kathryn Barker

Barker's academic background includes a PhD in Remote Sensing and Marine Optics (2004–2009), with her thesis entitled 'Novel Techniques to Estimate Primary Production directly from Earth Observation Data', supervised by Dr S. Lavender of the University of Plymouth, UK. Her research has centered on ocean colour remote sensing, developing methods to quantify marine primary production using satellite observations. More recently, she has contributed to computational marine ecology through collaborations at Curtin University's Institute for Computation. Key publications include co-authorship on 'Generalised deep learning model for semi-automated length measurement of fish in stereo-BRUVs' (Marrable et al., Frontiers in Marine Science, 2023), which presents a deep learning approach for accurate fish biometrics from baited remote underwater video systems; 'Accelerating Species Recognition and Labelling of Fish from Images' (Marrable et al., Frontiers in Marine Science, 2022), enhancing machine-assisted annotation for large-scale marine surveys; and 'Between a Reef and a Hard Place: Capacity to Map the Distribution of Reef Building Corals' (Hickey et al., Frontiers in Marine Science, 2020), assessing remote sensing potential for coral reef monitoring. Career highlights encompass serving as Project Manager for Data Services at Pawsey Supercomputing Research Centre (2015–2017), Project Manager at ARGANS Ltd (2008–2015), and roles at Curtin University. Her work bridges earth observation, supercomputing, and astronomy, impacting fields from marine science to astrophysics data management.