Stephen John Eglen

Stephen John Eglen is a Professor in Computational Biology at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge. He holds the position of Reader, focusing on computational neuroscience with expertise in retinal and visual pathway development. His research explores structural and functional aspects of neural circuit formation, including positional information in retinal neurons and synaptic connectivity mechanisms. Eglen is affiliated with the Computational Biology research group and has contributed to open science initiatives like CODECHECK and DeepClean.

His academic career includes roles as a Wellcome Trust Fellow (1997–2000), Lecturer at the University of Edinburgh (2000–2001), and Senior Lecturer at DAMTP (2006–2015). His work bridges computational methods with experimental neuroscience, emphasizing reproducible research practices and computational tools for data analysis.

Eglen's research interests span computational modeling of neural development, open science advocacy, and neurophysiological data analysis. He has published extensively on topics like retinal mosaics, neural network topology, and Bayesian statistical methods. His lab develops tools for analyzing neuronal activity in vitro and promoting transparency in scientific workflows.