CONI Lab develops neuroscience-inspired AI to understand and model human brain dynamics. By integrating computational modeling and multimodal biosignals, we translate these insights into clinically relevant neurotechnology and digital health solutions.
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Research Overview
Research Overview
CONI Lab investigates computational principles of human brain dynamics and translates them into interpretable Neuro-AI. By integrating multimodal biosignals and machine learning, we aim to build reliable and clinically relevant brain-state models for neurotechnology and digital health.
Our research integrates multimodal biosignals and computational modeling to understand and translate human brain dynamics. We focus on interpretable and generalizable Neuro-AI frameworks for clinical and neurotechnology applications.
Core Research Directions
Core Research Directions
Brain-State Modeling and Computational Biomarkers
We investigate computational principles underlying brain-state dynamics using multimodal biosignals and neuroimaging. Our goal is to identify robust and interpretable biomarkers that characterize cognitive, affective, and pathological states across diverse clinical conditions.
Multimodal Neuro-AI and Predictive Modeling
We develop machine learning frameworks that integrate electrophysiological signals, physiological data, and clinical variables to enable diagnosis, prognosis, and precision modeling of brain-related disorders. Emphasis is placed on generalizable and interpretable AI.
Neurotechnology and Human–AI Interaction
We design intelligent neurotechnologies, including brain–computer interfaces and adaptive monitoring systems, to translate brain-state decoding into real-world applications. Our work bridges neural signals, computational intelligence, and human-centered system design.
Methodological Approach
Methodological Approach
Multimodal data integration
Interpretable and causal modeling
Generalizable predictive learning
Cross-cohort and clinical validation
Expected Impact
Expected Impact
Our research advances brain–computer interaction, early detection of neurological conditions, and adaptive computational systems grounded in human brain dynamics.
Collaborations
Collaborations
Collaborating with leading academic and clinical institutions to advance translational Neuro-AI research.
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