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Aaditya V. Rangan, Ph.D.

Affiliations: 
2003 University of California, Berkeley, Berkeley, CA, United States 
Area:
Applied mathematics, Numerical analysis, Fast algorithms, Materials science
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"Aaditya Rangan"
Cross-listing: Materials Tree

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John Strain grad student 2003 UC Berkeley
 (Adaptive solvers for partial differential and differential -algebraic equations.)

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Publications

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Zhang J, Shao Y, Rangan AV, et al. (2019) A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs. Journal of Computational Neuroscience
Lei H, Yu Y, Zhu S, et al. (2016) Intrinsic and Network Mechanisms Constrain Neural Synchrony in the Moth Antennal Lobe. Frontiers in Physiology. 7: 80
Zhang JW, Rangan AV. (2015) A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony Journal of Computational Neuroscience. 38: 355-404
Zhang J, Zhou D, Cai D, et al. (2014) A coarse-grained framework for spiking neuronal networks: between homogeneity and synchrony. Journal of Computational Neuroscience. 37: 81-104
Zhang J, Newhall K, Zhou D, et al. (2014) Distribution of correlated spiking events in a population-based approach for Integrate-and-Fire networks. Journal of Computational Neuroscience. 36: 279-95
Zhou D, Rangan AV, McLaughlin DW, et al. (2013) Spatiotemporal dynamics of neuronal population response in the primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 110: 9517-22
Patel MJ, Rangan AV, Cai D. (2013) Coding of odors by temporal binding within a model network of the locust antennal lobe. Frontiers in Computational Neuroscience. 7: 50
Rangan AV, Young LS. (2013) Emergent dynamics in a model of visual cortex. Journal of Computational Neuroscience. 35: 155-67
Rangan AV, Young LS. (2013) Dynamics of spiking neurons: between homogeneity and synchrony. Journal of Computational Neuroscience. 34: 433-60
Rangan AV. (2012) Functional roles for synaptic-depression within a model of the fly antennal lobe. Plos Computational Biology. 8: e1002622
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