Chandrajit Bajaj

The paper shows that signed dopaminergic asymmetry correlates with contralateral motor laterality in Parkinson's disease, distinguishing mirror-image and conflicting states from mean-only summaries.

This paper introduces a probabilistic framework for analyzing motor states in Parkinson's disease, showing they are dynamic and associated with imaging features.

The paper introduces a pathway-anchored clustering framework to analyze multimodal imaging data in Parkinson's disease, identifying stable patient clusters and structure-function associations.

This paper introduces automated noise reduction methods for hyperspectral imaging data, achieving faster processing with comparable accuracy to manual methods.