Baskar Ganapathysubramanian
Cited by
Cited by
Sparse grid collocation schemes for stochastic natural convection problems
B Ganapathysubramanian, N Zabaras
Journal of Computational Physics 225 (1), 652-685, 2007
Machine learning for high-throughput stress phenotyping in plants
A Singh, B Ganapathysubramanian, AK Singh, S Sarkar
Trends in plant science 21 (2), 110-124, 2016
An explainable deep machine vision framework for plant stress phenotyping
S Ghosal, D Blystone, AK Singh, B Ganapathysubramanian, A Singh, ...
Proceedings of the National Academy of Sciences 115 (18), 4613-4618, 2018
Engineering fluid flow using sequenced microstructures
H Amini, E Sollier, M Masaeli, Y Xie, B Ganapathysubramanian, HA Stone, ...
Nature communications 4 (1), 1-8, 2013
Deep learning for plant stress phenotyping: trends and future perspectives
AK Singh, B Ganapathysubramanian, S Sarkar, A Singh
Trends in plant science 23 (10), 883-898, 2018
Computationally efficient solution to the Cahn–Hilliard equation: Adaptive implicit time schemes, mesh sensitivity analysis and the 3D isoperimetric problem
O Wodo, B Ganapathysubramanian
Journal of Computational Physics 230 (15), 6037-6060, 2011
Modeling diffusion in random heterogeneous media: Data-driven models, stochastic collocation and the variational multiscale method
B Ganapathysubramanian, N Zabaras
Journal of Computational Physics 226 (1), 326-353, 2007
Enhanced charge separation in organic photovoltaic films doped with ferroelectric dipoles
KS Nalwa, JA Carr, RC Mahadevapuram, HK Kodali, S Bose, Y Chen, ...
Energy & Environmental Science 5 (5), 7042-7049, 2012
Genome-wide association analysis of seedling root development in maize (Zea mays L.)
BGTL Jordon Pace, Candice Gardner, Cinta Romay
BMC Genomics 16 (47), 2015
A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach
N Zabaras, B Ganapathysubramanian
Journal of Computational Physics 227 (9), 4697-4735, 2008
Modeling morphology evolution during solvent-based fabrication of organic solar cells
O Wodo, B Ganapathysubramanian
Computational Materials Science 55, 113-126, 2012
Vertical phase separation in small molecule: polymer blend organic thin film transistors can be dynamically controlled
K Zhao, O Wodo, D Ren, HU Khan, MR Niazi, H Hu, M Abdelsamie, R Li, ...
Advanced Functional Materials 26 (11), 1737-1746, 2016
A real-time phenotyping framework using machine learning for plant stress severity rating in soybean
HS Naik, J Zhang, A Lofquist, T Assefa, S Sarkar, D Ackerman, A Singh, ...
Plant methods 13 (1), 1-12, 2017
A non-linear dimension reduction methodology for generating data-driven stochastic input models
B Ganapathysubramanian, N Zabaras
Journal of Computational Physics 227 (13), 6612-6637, 2008
Modelling dendritic solidification with melt convection using the extended finite element method
N Zabaras, B Ganapathysubramanian, L Tan
Journal of Computational Physics 218 (1), 200-227, 2006
Analysis of maize (Zea mays L.) seedling roots with the high-throughput image analysis tool ARIA (Automatic Root Image Analysis)
J Pace, N Lee, HS Naik, B Ganapathysubramanian, T Lübberstedt
PLoS One 9 (9), e108255, 2014
A graph-based formulation for computational characterization of bulk heterojunction morphology
O Wodo, S Tirthapura, S Chaudhary, B Ganapathysubramanian
Organic Electronics 13 (6), 1105-1113, 2012
Computer simulation of heterogeneous polymer photovoltaic devices
HK Kodali, B Ganapathysubramanian
Modelling and Simulation in Materials Science and Engineering 20 (3), 035015, 2012
Computer vision and machine learning for robust phenotyping in genome-wide studies
J Zhang, HS Naik, T Assefa, S Sarkar, RVC Reddy, A Singh, ...
Scientific Reports 7 (1), 1-11, 2017
A stochastic multiscale framework for modeling flow through random heterogeneous porous media
B Ganapathysubramanian, N Zabaras
Journal of Computational Physics 228 (2), 591-618, 2009
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