Dr Lucas França

Co Lead

A physicist by choice, a neuroscientist by fate, and a computer scientist by accident. Assistant Professor in Computer and Information Sciences at Northumbria University, with research spanning complex systems, computational neuroscience, and machine learning applied to sleep and circadian science.

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Biography

I like to describe myself as a physicist by choice, a neuroscientist by fate, and a computer scientist by accident. I am an Assistant Professor in Computer and Information Sciences at Northumbria University. My research interests include Complex Systems, Computational Neuroscience, and Machine Learning.

My doctoral work focused on the scaling and multifractal properties of intracranial electrophysiological signals in epilepsy — developing novel approaches to seizure detection and classification that extract clinically useful information from the heterogeneous dynamics of brain activity. Since then, my work has broadened to apply tools from physics and data science across a range of problems: dynamic functional connectivity in neonatal and preterm infants, actigraphy-based methods for studying circadian rhythms and physical activity, and the development of open, reproducible research infrastructure for chronobiology and sleep science.

Education

PhD in Computational Neuroscience - Scaling properties and heterogeneous dynamics of epileptic activity - University College London (London, UK - 2020)

MSc in Physics (Statistical Physics and Complex Systems) - Federal University of Bahia (Salvador, BR - 2015)

BSc in Physics - Federal University of Bahia (Salvador, BR - 2013)

Experience

Assistant Professor in Computer and Information Sciences - Northumbria University (Newcastle upon Tyne, UK | 2023 - Current)

Research Associate - King’s College London (London, UK | 2020 - 2023)

Research Assistant - King’s College London (London, UK | 2020 - 2020)

Selected Publications

Pugliane, K.C., França, L.G.S., Leocadio-Miguel, M.A. & Araújo, J.F. (2026). Low-latitude environmental regularity supports circadian organisation in blind adults. Chronobiology International.

Batista, E.D.S., Silva Gomes, S.R.B., de Morais Ferreira, A.B., França, L.G.S., et al. (2026). From movement to METs: A validation of ActTrust® for energy expenditure estimation and physical activity classification in young adults. PLoS One, 21(5).

França, L.G.S., Ciarrusta, J., Gale-Grant, O., Fenn-Moltu, S., et al. (2024). Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment. Nature Communications, 15, 16.

Gale-Grant, O., Fenn-Moltu, S., França, L.G.S., Dimitrova, R., et al. (2022). Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies. Human Brain Mapping, 43(5), 1577–1589.

Li, K., Vakharia, V.N., Sparks, R., França, L.G.S., et al. (2019). Optimizing Trajectories for Cranial Laser Interstitial Thermal Therapy Using Computer-Assisted Planning: A Machine Learning Approach. Neurotherapeutics, 16(1), 182–191.

França, L.G.S., Miranda, J.G.V., Leite, M., Sharma, N.K., Walker, M.C., Lemieux, L. & Wang, Y. (2018). Fractal and Multifractal Properties of Electrographic Recordings of Human Brain Activity: Toward Its Use as a Signal Feature for Machine Learning in Clinical Applications. Frontiers in Physiology, 9, 1767.

Costa, I., Gamundí, A., Miranda, J., França, L.G.S., De Santana, C. & Montoya, P. (2017). Altered Functional Performance in Patients with Fibromyalgia. Frontiers in Human Neuroscience, 11.