My cognitive neuroscience research harnesses cutting-edge artificial intelligence to enhance methodological precision and analytical depth in neuroimaging. A persistent challenge in the field is the scarcity and acquisition difficulty of task-based fMRI data. To address this limitation, we are developing a multimodal integration/inference framework that synthesizes MRI, EEG, fNIRS and cognitive behavioral measures, thereby expanding usable datasets through cross-modal inference techniques. Concurrently, I am developing a comprehensive end-to-end analysis pipeline that seamlessly connects neuroimaging outputs with statistical analysis platforms and interpretive databases, generating nuanced analytical summaries that facilitate deeper insights.