B. T. Thomas Yeo
Associate Professor
Leads the Computational Brain Imaging Group, developing machine learning to map individual brain networks and predict behaviour and mental disorder symptoms from MRI.
B. T. Thomas Yeo's lab at NUS works on neuroscience & brain-computer interfaces and medical imaging & healthcare AI. 63 papers since 2023, 1 at top venues, mostly NeurIPS. 10 PhD students. 12 alumni. Applications close .
At a glance
- papers, 2023–2026
- 16/ year
- at T1 venues
- 2%
- PhD students
- 10
- MS students
- 0
- alumni listed
- 12
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 12 papers2026 · T1 0 · collecting
- 21 papers2025 · T1 1
- 15 papers2024 · T1 0
- 15 papers2023 · T1 0
T1 venuesOtherVenues: NeurIPS
Research focuspaper titles that use each topic's words
- Neuroscience & brain-computer interfaces25 papers
- brain25 papers
- individual3 papers
- Medical imaging & healthcare AI2 papers
- brain imaging0 papers
Paper list
From the lab homepage and DBLP.
202612 papers
- —Associations between epilepsy-related polygenic risk and brain morphology in childhood
- —Atrophy in preclinical Alzheimer’s disease maps to a network that predicts longitudinal decline
- —Convergent and divergent brain–cognition development in early adolescence
- —From big to small: Emerging methods for enhancing precision psychiatry through transfer learning
- —Improved Reliability of Resting-State Functional MRI Connectivity Using Multi-Echo Acquisition: Implications for Personalized Transcranial Magnetic Stimulation Targeting
- —Individual‐specific resting‐state networks predict language dominance in drug‐resistant epilepsy
- —Leveraging Stacked Classifiers for Multi-task Executive Function in Schizophrenia Yields Diagnostic and Prognostic Insights
- —Multivariate associations of motor performance, sleep quality, depressive symptoms, and grey matter volume in younger and mid-to-older adults
- —Network-based near-scalp personalized brain stimulation targets
- —Neuroanatomy reflects individual variability in impulsivity in youth
- —Peripheral immune–redox signatures associate with cortical network alterations in anhedonic depression
- —Vascular age estimation using a consumer wearable sleep tracker
202521 papers
- —A network correspondence toolbox for quantitative evaluation of novel neuroimaging results
- —A pattern-learning algorithm associates copy number variations with brain structure and behavioural variables in an adolescent population cohort
- —Autonomic physiological coupling of the global fMRI signal
- —Benchmarking methods for mapping functional connectivity in the brain
- NeurIPS (T1)Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens (opens in a new tab)
- —Considering the interconnected nature of social identities in neuroimaging research
- —Cross-dataset Evaluation of Dementia Longitudinal Progression Prediction Models
- Medical Image Anal.DeepResBat: deep residual batch harmonization accounting for covariate distribution differences (opens in a new tab)
- —Distinct brain network features predict internalizing and externalizing traits in children, adolescents and adults
- —Distinct cognitive and functional connectivity features from healthy cohorts can identify clinical obsessive-compulsive disorder
- —HARMONISATION – A multimodal prospective study of vascular cognitive impairment in multi-ethnic Asians: Cohort profile, progress, current contributions, and future impact
- —High-Order Graphical Topology Analysis of Brain Functional Connectivity Networks Using fMRI
202415 papers
- —Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder
- —Differential spatial working memory-related functional network reconfiguration in young and older adults
- —Functional brain networks are associated with both sex and gender in children
- —Generalizable and replicable brain-based predictions of cognitive functioning across common psychiatric illness
- NeuroinformaticsGradients of Brain Organization: Smooth Sailing from Methods Development to User Community (opens in a new tab)
- —In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth
- —Macroscale intrinsic dynamics are associated with microcircuit function in focal and generalized epilepsies
- —Multilayer meta-matching: Translating phenotypic prediction models from multiple datasets to small data
- —Multimodal neural correlates of childhood psychopathology
- —Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function
- —Predicting an individual’s functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects
- —Structural covariation between cerebellum and neocortex intrinsic structural covariation links cerebellum subregions to the cerebral cortex
202315 papers
- —A critical period plasticity framework for the sensorimotor–association axis of cortical neurodevelopment
- —Adherence to 24-Hour Movement Recommendations and Health Indicators in Early Adolescence: Cross-Sectional and Longitudinal Associations in the Adolescent Brain Cognitive Development Study
- —Brain-based predictions of psychiatric illness-linked behaviors across the sexes
- NeuroImageComparison Between Gradients and Parcellations for Functional Connectivity Prediction of Behavior (opens in a new tab)
- —Controversies and progress on standardization of large-scale brain network nomenclature
- NeuroImageHomotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity (opens in a new tab)
- —Language network lateralization is reflected throughout the macroscale functional organization of cortex
- —Leveraging machine learning for gaining neurobiological and nosological insights in psychiatric research
- —Mapping human brain charts cross-sectionally and longitudinally
- SensorsNocturnal Blood Pressure Estimation from Sleep Plethysmography Using Machine Learning (opens in a new tab)
- —One Size Does Not Fit All: Methodological Considerations for Brain-Based Predictive Modeling in Psychiatry
- NeuroImageRelationship Between Prediction Accuracy and Feature Importance Reliability: an Empirical and Theoretical Study (opens in a new tab)
Where alumni went12 listed
Apply to NUSFall 2027
School of Computing PhD in Computer Science
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Not yet confirmed for this intake.
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