Month: November 2021

I am currently doing a PhD with Prof. Ronaldo Menezes and Prof. Hywel Williams in Computer Science at the University of Exeter, UK, where I study echo chambers formation in scientific collaboration networks.

I was born in Bogotá, Colombia. I graduated with an undergraduate and master’s degree in industrial engineering at the Universidad de Los Andes in 2017 and 2019, respectively. In 2017, together with my advisors Dr Felipe Montes and Professor Olga Lucía Sarmiento, I received third place for the best undergraduate thesis in social sciences in Colombia. In 2018 I was a visiting researcher at the Health Disparities & Cultural Identities Lab of the psychology department at Florida International University. The research trip was funded by a Bridge Grant from the Young researchers of the Complex Systems Society.

A great curiosity to understand human behaviour on a social and collective level has led me to work with engineering, psychology, social sciences, education, and public health researchers. I am interested in investigating higher education systems, sociology of science, public health, and social inequity from a complex systems approach, particularly network science.

Josh Buxton has recently published a paper which provides a method for quantifying the morphology of patterned vegetation and analyses the changing resilience of these sites over time using satellite data. You can find the work online.

Vegetation patterns form in dryland areas as a response to declining precipitation levels. They have also been hypothesised to be indicators of the resilience of the vegetation system. Previous studies have made this qualitative link and used models to quantitatively explore it, but few have quantitatively analysed available data to test the hypothesis. Here we provide methods for quantitatively monitoring the resilience of patterned vegetation, applied to 40 sites in the Sahel (a mix of previously identified and new ones).
We show that an existing quantification of vegetation patterns in terms of a feature vector metric can effectively distinguish gaps, labyrinths, spots, and a novel category of spot–labyrinths at their maximum extent, whereas NDVI does not. The feature vector pattern metric correlates with mean precipitation. We find that vegetation resilience is linked to precipitation, but we find no significant correlation between patter morphology and resilience.

James is a PhD student undertaking an EPSRC funded PhD titled: “Social and Environmental Data Science”, supervised by Prof. Hywel Williams, and Dr. Rudy Arthur.

His research interests include investigating alternative unstructured data sources for improving our understanding of natural hazards and climate change, specifically social media data.

After completing a Mathematics BSc and Data Science MSc from the University of Exeter, he worked as a research associate (RA) between 2020 and 2021 where his research projects included:
• Social Sensing Kerala Floods. This project compared government flood impact data for the 2018 Kerala flood to three social media data sources. Results showed strong agreement between the government data and social media data, with the latter sources enabling real-time monitoring for free.
• Social Sensing for Resilient Cities. Facebook data regarding extreme heat was collected and analysed, with a dashboard produced to highlight the cabability of social media data for improving our understanding of heatwaves. This was presented to resilience representatives from the London, Athens, and Hague councils.