Research
Publications
Baker B. , Pearlmutter B., Miller R., Calhoun V.D, Plis S., "Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse"
Baker B. , Salman M., Fu Z.,Iraji A.,Osuch E.,Bockholt H. J.,Calhoun V.D, 2023. "MULTISCALE NEUROIMAGING FEATURES FOR THE IDENTIFICATION OF MEDICATION CLASS AND NON-RESPONDERS IN MOOD DISORDER TREATMENT". Preprint (2023)
Baker B. "LEARNING WITH LESS: LOW-RANK DYNAMICS, COMMUNICATION, AND
INTROSPECTION IN NEUROIMAGING." PhD Dissertation (2023)
Verner E., Petropoulous H., Baker B. , Bockholt H.J., Fries J., Bohsali A., Raja R., Trinh D.H, Calhoun V.D., "Brainforge: An online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing." Concurrency and Computation: Practice and Experience 35.18 (2023): e6855.
Salman, M. S., Verner, E., Bockholt, H. J., Fu, Z., Misiura, M., Baker, B. T. , ... & Calhoun, V. D. (2023). Multi-study evaluation of neuroimaging-based prediction of medication class in mood disorders. Psychiatry Research: Neuroimaging, 333, 111655.
Panichvatana, C. A., Chen, J., Baker, B. , Thapaliya, B., Calhoun, V., & Liu, J. (2023, July). Decentralized Parallel Independent Component Analysis for Multimodal, Multisite Data. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1-4). IEEE.
Martin, D., Basodi, S., Panta, S., Rootes-Murdy, K., Prae, P., Sarwate, A. D., Romero, K., Baker, B.T., Gazula, H., Bockholt, H.J., Calhoun, V. D. (2023). "Enhancing collaborative neuroimaging research: introducing COINSTAC
Vaults for federated analysis and reproducibility."" Frontiers in Neuroinformatics, 17, 1207721.
Motlaghian, S. M., Vahidi, V., Baker, B. , Belger, A., Bustillo, J. R., Faghiri, A., ... & Calhoun, V. D. (2023). A method for estimating and characterizing explicitly nonlinear dynamic functional network connectivity in resting-state fMRI data. Journal of Neuroscience Methods, 389, 109794.
Baker B. , Pearlmutter B., Calhoun V., Plis S.,
"Peering Beyond the Gradient Veil with Distributed Auto-Differentiation." Arxiv Preprint (2022)
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
Theses
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) mrn.org for more information.
Other Areas of Interest
Philosophy of Mathematics, Political Philosophy, Multi-Modal Data Analysis
Home LinkedIn GitHub