| 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 | 1105 | 2016 |
| 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 | 596 | 2018 |
| 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 | 566 | 2018 |
| Sparse grid collocation schemes for stochastic natural convection problems B Ganapathysubramanian, N Zabaras Journal of Computational Physics 225 (1), 652-685, 2007 | 536 | 2007 |
| Plant disease identification using explainable 3D deep learning on hyperspectral images K Nagasubramanian, S Jones, AK Singh, S Sarkar, A Singh, ... Plant methods 15, 1-10, 2019 | 358 | 2019 |
| Nanoscale control of internal inhomogeneity enhances water transport in desalination membranes TE Culp, B Khara, KP Brickey, M Geitner, TJ Zimudzi, JD Wilbur, SD Jons, ... Science 371 (6524), 72-75, 2021 | 274 | 2021 |
| 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, 1-12, 2017 | 209 | 2017 |
| Engineering fluid flow using sequenced microstructures H Amini, E Sollier, M Masaeli, Y Xie, B Ganapathysubramanian, HA Stone, ... Nature communications 4 (1), 1826, 2013 | 208 | 2013 |
| Challenges and opportunities in machine-augmented plant stress phenotyping A Singh, S Jones, B Ganapathysubramanian, S Sarkar, D Mueller, ... Trends in Plant Science 26 (1), 53-69, 2021 | 192 | 2021 |
| A weakly supervised deep learning framework for sorghum head detection and counting S Ghosal, B Zheng, SC Chapman, AB Potgieter, DR Jordan, X Wang, ... Plant Phenomics, 2019 | 191 | 2019 |
| 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 | 188 | 2011 |
| Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems K Nagasubramanian, S Jones, S Sarkar, AK Singh, A Singh, ... Plant methods 14, 1-13, 2018 | 187 | 2018 |
| Crop yield prediction integrating genotype and weather variables using deep learning J Shook, T Gangopadhyay, L Wu, B Ganapathysubramanian, S Sarkar, ... Plos one 16 (6), e0252402, 2021 | 182 | 2021 |
| 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 | 177 | 2015 |
| Modeling morphology evolution during solvent-based fabrication of organic solar cells O Wodo, B Ganapathysubramanian Computational Materials Science 55, 113-126, 2012 | 146 | 2012 |
| 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 | 143 | 2012 |
| 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 | 135 | 2007 |
| 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 | 131 | 2014 |
| 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 | 129 | 2016 |
| 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 | 129 | 2008 |
Soumik SarkarDirector, Translational AI Center, Professor, Iowa State UniversityVerified email at iastate.edu
