Baskar Ganapathysubramanian

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Soumik SarkarDirector, Translational AI Center, Professor, Iowa State UniversityVerified email at iastate.edu
Asheesh K. SinghProfessor, Iowa State University; Co-Director, Iowa Soybean Research CenterVerified email at iastate.edu
Olga WodoUniversity at Buffalo, Materials Design and Innovation DepartmentVerified email at buffalo.edu
Adarsh KrishnamurthyIowa State UniversityVerified email at iastate.edu
Chinmay HegdeNew York UniversityVerified email at nyu.edu
Patrick SchnableIowa State UniversityVerified email at iastate.edu
Dino Di CarloProfessor of Bioengineering, UCLAVerified email at seas.ucla.edu
Hari SundarAssociate Professor, School of Computing, University of UtahVerified email at cs.utah.edu
Ming-Chen HsuProfessor of Mechanical Engineering at Iowa State UniversityVerified email at iastate.edu
Robbyn AnandAssociate Professor of Chemistry, Iowa State UniversityVerified email at iastate.edu
Ulrike PasseIowa State UniversityVerified email at iastate.edu
Chad RiskoUniversity of KentuckyVerified email at uky.edu
Enrique D GomezProfessor of Chemical Engineering and Materials Science and Engineering, The Pennsylvania StateVerified email at psu.edu
Aram AmassianProfessor of Materials Science and Engineering, North Carolina State UniversityVerified email at ncsu.edu
Michael ChabinycUniversity of California Santa BarbaraVerified email at engineering.ucsb.edu
James RossmanithIowa State UniversityVerified email at iastate.edu
Surya R. KalidindiGeorgia Institute of Technology, Atlanta, GAVerified email at me.gatech.edu
Masayuki HirafujiUniv. of Tokyo (Prof.), Dream Science Holdings (CEO)Verified email at evolution-lab.com
Seishi NinomiyaThe University of TokyoVerified email at g.ecc.u-tokyo.ac.jp
Dean M DeLongchamp or Dean DeLo...NISTVerified email at nist.gov

Baskar Ganapathysubramanian

NSF/USDA AI Institute, Iowa State University

Verified email at iastate.edu - Homepage

Computational science Transport phenomena Energy technology Machine learning


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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	1051	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	564	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	528	2018
Sparse grid collocation schemes for stochastic natural convection problems B Ganapathysubramanian, N Zabaras Journal of Computational Physics 225 (1), 652-685, 2007	528	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	314	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	239	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	205	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	198	2013
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	187	2011
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	176	2019
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	173	2015
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	171	2018
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	158	2021
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	142	2021
Modeling morphology evolution during solvent-based fabrication of organic solar cells O Wodo, B Ganapathysubramanian Computational Materials Science 55, 113-126, 2012	141	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	140	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	139	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	130	2014
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	128	2008
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), 44048, 2017	125	2017

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