Research

I pursue research in the areas of Network Neuroscience and Complex Network analysis.  Human brain is organized into functional regions specialized for different functions. Using functional Magnetic Resonance Imaging (fMRI) on brain, one can obtain time series of neuronal activations for different volume elements, ‘voxels’, in the brain. Functional connectivity between regions in the brain is measured by the correlation of time-series of different brain regions.  This data can be modelled as a network with the regions in the brain denoted by the network’s nodes and the functional relation between the regions denoted by the edges between the nodes. We attempt to detect the modular architecture of the brain. Extracting modules from the brain is a challenge due to limitations of fMRI, noisy data, high density of connections, weighted edges in the resultant brain networks. Our aim is to detect the modular structure in the brain, study its different characteristics and determine how it varies with age, sex and in neurodegenerative disease. You can view my CV here.

Publications:

  • Sukrit Gupta and Rajapakse, Jagath C. “Nodal Degree Distributions of Resting-State Functional Brain Modules” IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), IEEE, 2018.
  • Rajapakse, Jagath C., Sukrit Gupta, and Xiuchao Sui. “Fitting networks models for functional brain connectivity.”  IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), IEEE, 2017.
  • Sukrit, Gupta, Puzis Rami, and Kilimnik Konstantin. Comparative Network Analysis Using KronFit. Complex Networks VII 644 (2016): 363.  (2016)
  • Goel, K., Singh, R. R., Iyengar, S. R. S., & Gupta, S. (2015). A faster algorithm to update betweenness centrality after node alteration. Internet Mathematics


Lists for Ranking of Conferences
SCSE NTU Ranking for Conferences and Journals
GGS Conference Rating
CORE Conference Ranking
Conference Ranking By Prof Osmar from UAlberta

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