David C Sterratt

David C Sterratt is a Lecturer in the School of Informatics at the University of Edinburgh, affiliated with the Institute for Adaptive and Neural Computation. He serves as Deputy Director of Learning & Teaching (Operations) and has been a faculty member since 2000. His academic background includes a PhD in computational neuroscience and an undergraduate degree in Physics.

His research centers on computational neuroscience, particularly multiscale modeling of neurons, synaptic plasticity, and the development of neural topographic maps. He has developed key software tools such as Retistruct for reconstructing retinal anatomy and KappaNEURON for integrating stochastic rule-based models with deterministic neuronal simulations. His work bridges molecular-level biochemical networks and electrical activity in neurons, offering insights into how synaptic proteomes interact with neuronal dynamics.

Dr. Sterratt's teaching focuses on data science, statistics, and sustainability. He co-designed and organizes the large second-year undergraduate course Informatics 2 - Foundations of Data Science and teaches the new course Modelling of Systems for Sustainability. He supervises undergraduate and postgraduate projects and is open to PhD supervision, currently co-supervising students Domas Linkevicius and Susana Román García.

His recent publications reveal a strong trend in integrating multi-level biological data into computational models, particularly in retinotopic map formation, synaptic scaling, and familiarity memory. These works combine mathematical modeling, simulation, and analysis to address fundamental questions in neural development and function.

• Fellow of the Higher Education Academy (HEA)

Dr. Sterratt has been actively involved in academic leadership and sustainability initiatives, having served as Energy Coordinator for the Informatics Forum from 2011 to 2019. He has secured research funding through collaborations and software development, and his textbook Principles of Computational Modelling in Neuroscience (with Bruce Graham, Andrew Gillies, Gaute Einevoll, and David Willshaw) is a key educational resource in the field. He is a dedicated mentor and educator, contributing significantly to curriculum development and student training.

He is part of the Institute for Adaptive and Neural Computation, a leading research group in neural computation and machine learning, and collaborates extensively with researchers such as David Willshaw, Bruce Graham, and Arjen van Ooyen. His work continues to advance the integration of molecular, cellular, and systems-level neuroscience through computational approaches.