Anand D. Sarwate

This paper explores privacy-preserving visualization techniques for brain functional connectivity using differential privacy to protect participant data while maintaining visual utility.

NeuroFLAME provides a secure, scalable federated platform for multi-site neuroimaging analysis, achieving consistency with centralized methods while preserving data privacy and enabling institutional compliance.

This paper introduces COINSTAC Vaults to enhance collaborative neuroimaging research through federated analysis and reproducibility by hosting standardized datasets.

This study uses federated analysis in COINSTAC to examine functional network connectivity in adolescent brains linked to smoking and alcohol consumption, finding hypoconnectivity and reduced synchronization.

This work proposes a decentralized method for brain age estimation using MRI data and shows it achieves similar performance to centralized models.

The paper introduces decentralized quality control tools for neuroimaging data in federated environments, showing promising results in visualization and outlier detection while preserving privacy.

This paper uses COINSTAC to perform decentralized VBM analysis on multi-site neuroimaging data to identify age, BMI, and smoking-related structural brain changes.