Bradley T. Baker



Baker B., Pearlmutter B., Calhoun V., Plis S., "Efficient Distributed Auto-Differentiation." Arxiv Preprint (2021)

Hassanzadeh, R., Silva, R.F., Abrol, A., Salman, M., Bonkhoff, A., Du, Y., Fu, Z., DeRamus, T., Damaraju, E., Baker, B. and Calhoun, V.D., 2021. Individualized Spatial Network Predictions Using Siamese Convolutional Neural Networks: A Resting-State fMRI Study of over 11,000 Unaffected Individuals. bioRxiv..

Gazula, H., Kelly, R., Romero, J., Verner, E., Baker, B.T., Silva, R.F., Imtiaz, H., Saha, D.K., Raja, R., Turner, J.A. and Sarwate, A.D., 2020. COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. Journal of Open Source Software, 5(54), p.2166.

Baker, B.T., Damaraju, E., Silva, R.F., Plis, S.M. and Calhoun, V.D., 2020. Decentralized dynamic functional network connectivity: State analysis in collaborative settings. Human brain mapping, 41(11), pp.2909-2925.

Imtiaz, H., Mohammadi, J., Silva, R., Baker, B., Plis, S.M., Sarwate, A.D. and Calhoun, V., 2019. Improved Differentially Private Decentralized Source Separation for fMRI Data. arXiv preprint arXiv:1910.12913.

Baker, B.T., Abrol, A., Silva, R.F., Damaraju, E., Sarwate, A.D., Calhoun, V.D. and Plis, S.M., 2019. Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. NeuroImage, 186, pp.557-569.

Gazula, H., Baker, B. et al. "Decentralized Analysis of Brain Imaging Data: Voxel-based Morphometry and Dynamic Functional Network Connectivity." Frontiers in Neuroinformatics 12 (2018): 55.

Baker, B., Silva, R., Sarwate A., Plis, S., Calhoun, V. (2015) "Large Scale Collaboration with autonomy: a case of distributed ICA"
Accepted to IEEE:MLSP 2015

Imtiaz, H., Sarwate A., Baker B., Silva R., Plis S., Calhoun V. (2016) “Privacy-preserving source separation for distributed data using independent component analysis”
Accepted to CISS 2016


Baker, B. (2016) “djICA: A New Algorithm for Decentralized Independent Component Analysis”

Baker, B. (2016) “Belief, Construction, and Language: Philosophical Lenses on Issues of Understanding and Cognition in Mathematics”

Areas of Interest/Ongoing Research

Distributed Deep Learning*

Deep Learning for Privacy Sensitive Applications

Information Ethics* and the Philosophy of Privacy

Using Machine Learning to Model Complex Adaptive Systems*

Mathematics and Deleuzian Rhizomatics*

* - indicates an area with an ongoing/submitted publication.
Draft manuscripts may be available depending on the publication venue/ date of submission/acceptance.
Contact bbaker (at) for more information.

Other Areas of Interest

Philosophy of Mathematics, Political Philosophy, Multi-Modal Data Analysis