Katarina Moravkova
MSc, BSc
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Katarina’s research work in the group focuses on two main tasks: first, to statistically validate a newly developed version of the stand level M1 growth and yield model, M1v2, using various data analysis techniques (e.g. regression analysis) and programming environments (e.g. C++, R); and second, to analyse and statistically model the potential influence of policy-driven and economic factors on forest management as potential drivers of carbon emissions in the UK.
Katarina joined FR in April 2023 and is currently completing her PhD in computational neuroscience at the University of Glasgow, Scotland. Her work focused on developing forward-modelling techniques characterising time series data of human brain activity to deepen our understanding of how the human brain responds to certain properties of visual stimuli. Her work consisted of using standardised statistical approaches (e.g. linear mixed-effects models, machine learning) and simulation work to uncover anomalies and patterns in spatial data representing different visual areas of the human brain. She completed her MSc and BSc, also at The University of Glasgow, in Research Methods of Psychological Science and Neuroscience, respectively, with a focus on quantitative methods and the use of functional magnetic resonance imaging (fMRI) and transcranial alternating current stimulation (tACS) in characterising human vision, sensorimotor integration and attention.
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