Baskar Ganapathysubramanian

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Soumik SarkarDirector, Translational AI Center, Professor, Iowa State UniversityVerifierad e-postadress på iastate.edu
Asheesh K. SinghProfessor, Iowa State University; Co-Director, Iowa Soybean Research CenterVerifierad e-postadress på iastate.edu
Olga WodoUniversity at Buffalo, Materials Design and Innovation DepartmentVerifierad e-postadress på buffalo.edu
Adarsh KrishnamurthyIowa State UniversityVerifierad e-postadress på iastate.edu
Chinmay HegdeNew York UniversityVerifierad e-postadress på nyu.edu
Patrick SchnableIowa State UniversityVerifierad e-postadress på iastate.edu
Hari SundarAssociate Professor, Computer Science, Tufts UniversityVerifierad e-postadress på tufts.edu
Ming-Chen HsuProfessor of Mechanical Engineering at Iowa State UniversityVerifierad e-postadress på iastate.edu
Robbyn AnandAssociate Professor of Chemistry, Iowa State UniversityVerifierad e-postadress på iastate.edu
Chad RiskoUniversity of KentuckyVerifierad e-postadress på uky.edu
Ulrike PasseIowa State UniversityVerifierad e-postadress på iastate.edu
Enrique D GomezProfessor of Chemical Engineering and Materials Science and Engineering, The Pennsylvania StateVerifierad e-postadress på psu.edu
Aram AmassianProfessor of Materials Science and Engineering, North Carolina State UniversityVerifierad e-postadress på ncsu.edu
Michael ChabinycUniversity of California Santa BarbaraVerifierad e-postadress på engineering.ucsb.edu
Surya R. KalidindiGeorgia Institute of Technology, Atlanta, GAVerifierad e-postadress på me.gatech.edu
Dean M DeLongchamp or Dean DeLo...NISTVerifierad e-postadress på nist.gov
Zhenan BaoStanford UniversityVerifierad e-postadress på stanford.edu
Ali ManiAssociate Professor of Mechanical Engineering, Stanford UniversityVerifierad e-postadress på stanford.edu
Christopher M. BatesUniversity of California, Santa BarbaraVerifierad e-postadress på ucsb.edu
Wei Guo（郭威）The University of TokyoVerifierad e-postadress på g.ecc.u-tokyo.ac.jp

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Baskar Ganapathysubramanian

NSF/USDA AI Institute, Iowa State University

Verifierad e-postadress på iastate.edu - Startsida

Computational science Transport phenomena Energy technology Machine learning


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
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	1087	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	590	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	558	2018
Sparse grid collocation schemes for stochastic natural convection problems B Ganapathysubramanian, N Zabaras Journal of Computational Physics 225 (1), 652-685, 2007	530	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	339	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	256	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	211	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	203	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	189	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	182	2019
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	182	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	178	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	175	2015
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	168	2021
Modeling morphology evolution during solvent-based fabrication of organic solar cells O Wodo, B Ganapathysubramanian Computational Materials Science 55, 113-126, 2012	143	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	141	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	140	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	134	2014
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	129	2017
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

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