KongFatt Wong-Lin
Research areas: Neuroscience · Cognitive Neuroscience · Neural dynamics and brain function · Dementia and Cognitive Impairment Research · Neural and Behavioral Psychology Studies
0000-0001-8724-4398
About
KongFatt Wong-Lin is a Professor of Computational Neuroscience and Machine Intelligence. He leads the NeuroAI and Neurotechnology research team at the Intelligent Systems Research Centre in Ulster University. His research interests span computational modelling and mathematical analysis in systems and cognitive neuroscience, psychology, brain disorders, neural computation and engineering, AI, and data science. He received his Ph.D. in Physics with focus on Computational Neuroscience at Brandeis University, with affiliation to the Volen National Center for Complex Systems. He was later a research associate at Princeton University, with affiliation to The Program in Applied and Computational Mathematics, and Princeton Neuroscience Institute. He has also received visiting fellowships at the University of Galway and University of Oxford.
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Publications (216)
- Mapping brain networks underlying abstract perceptual decision formation and its EEG signatures Save
- Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG Save
- A Paralinguistic Audio–Language Modeling for Zero-Shot Cross-Lingual Alzheimer's Detection Save
- A hybrid gaze-motor imagery BCI framework for effective decision communication Save
- A paralinguistic audio–language modeling for zero-shot cross-lingual Alzheimer’s detection Save
- Decision Confidence Neuron in Echo State Network for Continual Evaluation of EEG Motor Imagery Classification Quality Save
- Synergizing Zero-Shot Cross-Lingual Alzheimer Detection with Language Invariant Multimodal Bi-Geometric Adversarial Learning Save
- A Hybrid Gaze-Motor Imagery BCI Framework for Effective Decision Communication Save
- Human-Like Decision Uncertainty in a Minimal Dynamical Neural Network Model Save
- Multi-Objective Optimisation with Oscillatory Dynamics in Spontaneous and Decision Spiking Neural Networks Save
- Multi-Objective Optimisation with Oscillatory Dynamics in Spontaneous and Decision Spiking Neural Networks Save
- Limitations of Variational Laplace-Based Dynamic Causal Modelling for Multistable Cortical Circuits Save
- Machine Learning Applications for Brain Disorders: Towards Inclusivity and Equity Save
- Classifying Decision-Based Effector Modalities from Fragmented iEEG via Dynamic Recursive Feature Elimination Save
- Fatigue-Aware BCI for Adaptive Neurorehabilitation: Towards Personalised Stroke Therapy Save
- Neural oscillation as a selective modulatory mechanism on decision confidence, speed and accuracy Save
- Classifying decision-based effector modalities from fragmented iEEG via dynamic recursive feature elimination Save
- Toward interpretable schizophrenia detection from EEG using autoencoder and EfficientNet Save
- Neural Circuit with Top-down Inhibitory Feedback Outperforms Optimal Bayesian Integration in Multisensory Integration Save
- Minimal mean-field gated parietal circuit model for flexible perceptual decisions Save