Computational Movement Ecology Group

Colin Torney

Colin is a Professor in Applied Mathematics in the School of Mathematics and Statistics at the University of Glasgow. He completed his PhD in Applied and Computational Mathematics in 2009 at University College, Dublin and also holds a Masters degree in Engineering from Liverpool University and an MSc in Computational Science from UCD.

Colin's background is in mathematics and high performance computing but now has a strong applied focus in the areas of movement ecology, data science, and AI. In previous roles, he has been a software developer for a financial risk company, a risk analyst for a multi-national hedgefund, and an English and I.T. teacher in Pangani, Tanzania.

Cyrus Kavwele

Cyrus M. Kavwele is a PhD student in the School of Biodiversity, One Health, and Veterinary Medicine at the University of Glasgow.

Broadly, he is interested in understanding the role of and the mechanisms that drive collective behaviour of group navigating ungulate species and their response to ecosystem disturbances largely due to human activities. In his PhD, he is working on collective behaviour of wildebeests in Serengeti National Park in Tanzania. Majorly, his work focuses on developing an automated animal tracking tool using open-source electronics and UAVs to collect scale-appropriate data as well as application of computer vision and machine learning to examine complex behaviours such information transfer, collective decision making, leadership roles within a groups and spatial aggregation among others.

Cyrus has BSc. and MSc. degrees in wildlife management from Karatina University, Kenya where he also works as a Tutorial Fellow in the Department of Natural Resources. Outside science, Cyrus plays football whenever possible and enjoys camping on an occasional basis. Twitter @cyruskavwele

Jennifer Gaskell

Jenn is a Research Fellow in Mathematical Biology in the School of Mathematics and Statistics. She completed her PhD in Theoretical Physics in 2016 at The University of Nottingham.

Jenn's research focuses on the advancement of approximate Bayesian inference techniques through coupling with machine-learning techniques such as Gaussian processes and graph neural networks. She builds agent-based models of complex systems, such as collective movement models of migratory species in order to test and compare the performance of the inference frameworks. These frameworks can be applied to many systems, particularly across biological sciences.

Majaliwa Masolele

Majaliwa M. Masolele is a PhD student in Mathematical Ecology in the School of Statistics and Mathematics at the University of Glasgow with an interest in animal movement, quantitative ecology, geographic and spatial ecology, biostatistics, and machine learning.

His PhD is primarily focused on developing data driven models for migratory animal populations to answer fundamental ecological questions such as; how do animals modify their use of time when confronted with different environmental conditions, how do animals select a certain part of the landscape based on energetic considerations, or what will happen to migratory animals if a river dries, a large percent of the protected area is burned, or if food becomes scarce due to prolonged drought? This will be useful particularly in making informed conservation planning and conservation management techniques.

Mikolaj Kundergorski

Miks is a PhD student in applied mathematics looking at collective behaviour of Atlantic Salmon during downstream migration. He aims to create models that take into account group decision making for both laboratory experiments and river telemetry data. His background is in Computer Vision and he also works on refining object detection and tracking algorithms for ecological applications.

Nazareno Campioni

Nazareno is a PhD student in the School of Mathematics and Statistics at the University of Glasgow, specialising in Applied Mathematics. His primary research area is Mathematical Ecology, with a particular emphasis on collective behaviour.

His work majorly revolves around the analysis of animal telemetry data. His main goal is to develop novel mathematical and statistical models that can effectively extract more information out of relocation data. His specific focus lies in gaining a deeper understanding of the underlying factors that influence and shape the quantitatively and qualitatively distinct patterns of movement observed among animals.

Nazareno's research also involves studying a dataset of free-roaming Merino sheep in Patagonia. He examines the ecological behaviour of this flock with the primary objective of determining whether there is evidence of a leader-follower dynamic within the group.

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