Rickson C. Mesquita
Associate Professor
School of Computer Science
University of Birmingham
About
I am an Associate Professor of Computer Science at the University of Birmingham, UK. My research explores how to extract trustworthy physiological information from near-infrared light, robustly enough to use across time, people, and clinical settings. I develop computational methods, inference frameworks, and experimental protocols that make diffuse optical measurements more accurate, precise, and physiologically meaningful.
My work focuses on diffuse optics, particularly diffuse correlation spectroscopy (DCS), functional near-infrared spectroscopy (fNIRS), and time- and frequency-domain optical spectroscopy (TD/FD-DOS), with applications in brain injury, neurodegenerative disorders, mental health, and the study of learning and cortical plasticity. I am especially interested in biophysical modelling, physics-informed machine learning, and probabilistic inference, as well as in education: my teaching is shaped by cognitive neuroscience and data-driven learning analytics, and I work on STEM learning approaches that connect research and teaching.
Research Interests
Trustworthy physiological information in diffuse optics
Developing and validating methods to extract blood flow and oxygen metabolism from DOS, fNIRS, and speckle-based methods. Forward and inverse modelling, calibration, and the physics of what near-infrared light actually encodes in tissue.
Principled uncertainty and reproducibility
Probablistic inference frameworks for optical time series that produce honest posterior distributions rather than point estimates. Protocol design as a computational optimisation problem: building acquisition and analysis systems whose variability is smaller than the biological signal of interest.
Physics-informed computation
Machine learning and signal processing methods constrained by biophysical forward models – combining the flexibility of data-driven inference with the interpretability and physical plausibility that tissue optics demands. Applications include data denoising, optical property estimation, and haemodynamic modelling.
Longitudinal brain monitoring and plasticity
Using trustworthy optical measurements to track brain health over time – in brain injury, neurodegeneration, and mental health – and to study how the brain changes with learning. This is one application that motivates the methods I develop and tests whether the framework actually works in real-world settings.
STEM education and cognitive neuroscience
Developing and evaluating STEM learning approaches informed by cognitive neuroscience and data-driven educational analytics. My teaching and research inform each other: understanding how the brain learns is both a scientific question and a pedagogical one.
Latest Publications
V. Sánchez, S. Novi, A. C. Carvalho, A. Quiroga, R. M. Forti, F. Cendes, C. L. Yasuda, R. C. Mesquita (2026). Graph analysis of age-related changes in resting-state functional connectivity measured with fNIRS. J. Ageing Longev. [link]
P. D. Mc Entee, R. C. Mesquita, C. Delaney, E. Murphy, P. A. Boland, R. A. Cahill (2026). The evaluation of cognitive workload associated with indocyanine green fluorescence angiography in colorectal surgery. Surgical Endoscopy [link]
D. G. S. Machado, M. J. L. Melo, M. A. Mendonça, D. M. Leiros, E. B. Silva, R. M. Forti, R. C. Mesquita, H. Faro, O. E. Acevedo (2025). Effect of tDCS targeting the dorsolateral prefrontal cortex on psychophysiological responses and brain oxygenation during exercise in healthy adults: a proof-of-concept randomized controlled trial. Frontiers in Physiology [link]
J. Cao, S. Montero-Hernandez, R. C. Mesquita, A. T. Eggebrecht, H. Dehghani (2025). NIRFASTerFF: an accessible, cross-platform Python package for fast photon modelling. J. Biomedical Optics [link]
M. C. Lindino, L. F. Bortoletto, B. S. de Lima, A. Soriano-Vargas, R. C. Mesquita, A. Rocha (2025). Distinguishing stressor, stress, and state-anxiety: semantic and physiological insights with machine learning approaches. IEEE Sensors Journal [link]
Noteworthy Publications
M. A. Yücel, R. Luke, R. C. Mesquita, A. von Lühmann et al. (2025). fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience. Communications Biology [link]
K. Kazazian, A. Abdalmalak, S. L. Novi, L. Norton, R. Moulavi-Ardakani, M. Kolisnyk, T. E. Gofton, R. C. Mesquita, A. M. Owen, D. B. Debicki (2024). Functional near-infrared spectroscopy: a novel tool for detecting consciousness after acute severe brain injury. PNAS [link]
H. Ayaz et al. (2022). Optical imaging and spectroscopy for the study of the human brain: status report. Neurophotonics [link]
W. B. Baker et al. (2017). Noninvasive optical monitoring of critical closing pressure and arteriole compliance in human subjects. J. Cereb. Blood Flow Metab. [link]
S. L. Novi, R. B. M. L. Rodrigues, R. C. Mesquita (2016). Resting state connectivity patterns with near-infrared spectroscopy data of the whole head. Biomed. Opt. Express [link]
C. G. Favilla, R. C. Mesquita, M. Mullen et al. (2014). Optical bedside monitoring of cerebral blood flow in acute ischemic stroke patients during head-of-bed manipulation. Stroke [link]
R. C. Mesquita, A. D’Souza, T. V. Bilfinger et al. (2013). Optical monitoring and detection of spinal cord ischemia. PLOS One [link]
R. C. Mesquita, T. Durduran, G. Yu, . M. Buckley, M. N. Kim, C. Zhou, R. Choe, U. Sunar, A. G. Yodh (2011). Direct measurement of tissue blood flow and metabolism with diffuse optics. Phil. Trans. Royal Soc. A [link]
R. C. Mesquita, A. G. Yodh (2011). Diffuse Optics: fundamentals and tissue applications. Proceedings of the International School of Physics “Enrico Fermi” [link]
R. C. Mesquita, M. A. Franceschini, D. A. Boas (2010). Resting state functional connectivity of the whole head with near-infrared spectroscopy. Biomed. Opt. Express [link]
R. C. Mesquita, T. J. Huppert, D. A. Boas (2009). Exploring neuro-vascular and neuro-metabolic coupling in rat somatosensory cortex. Phys. Med. Biol. [link]
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Address
Edgbaston, Birmingham, UK B15 2TT