Baskar Ganapathysubramanian

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Featured Co-authors

Minsu Cho
74 publications
Soumik Sarkar
71 publications
Aarti Singh
71 publications
Chinmay Hegde
68 publications
Chao Liu
59 publications
Rahul Singh
50 publications
Aditya Balu
27 publications
Sourabh Bhattacharya
27 publications
Adarsh Krishnamurthy
22 publications
Victor M. Calo
19 publications
Ameya Joshi
16 publications

research

∙ 09/20/2023

Latent Diffusion Models for Structural Component Design

Recent advances in generative modeling, namely Diffusion models, have re...

0 Ethan Herron, et al. ∙

research

∙ 09/04/2023

Towards Foundational AI Models for Additive Manufacturing: Language Models for G-Code Debugging, Manipulation, and Comprehension

3D printing or additive manufacturing is a revolutionary technology that...

0 Anushrut Jignasu, et al. ∙

research

∙ 07/04/2023

Optimal Surrogate Boundary Selection and Scalability Studies for the Shifted Boundary Method on Octree Meshes

The accurate and efficient simulation of Partial Differential Equations ...

0 Cheng-Hau Yang, et al. ∙

research

∙ 07/03/2023

Space-time finite element analysis of the advection-diffusion equation using Galerkin/least-square stabilization

We present a full space-time numerical solution of the advection-diffusi...

0 Biswajit Khara, et al. ∙

research

∙ 06/04/2023

Deep learning powered real-time identification of insects using citizen science data

Insect-pests significantly impact global agricultural productivity and q...

0 Shivani Chiranjeevi, et al. ∙

research

∙ 05/30/2023

Generating Finite Element Codes combining Adaptive Octrees with Complex Geometries

We present a high-level domain-specific language (DSL) interface to driv...

0 Eric Heisler, et al. ∙

research

∙ 05/10/2023

Geometric Modeling and Physics Simulation Framework for Building a Digital Twin of Extrusion-based Additive Manufacturing

Accurate simulation of the printing process is essential for improving p...

0 Dhruv Gamdha, et al. ∙

research

∙ 05/02/2023

Out-of-distribution detection algorithms for robust insect classification

Deep learning-based approaches have produced models with good insect cla...

0 Mojdeh Saadati, et al. ∙

research

∙ 01/14/2023

Direct numerical simulation of electrokinetic transport phenomena: variational multi-scale stabilization and octree-based mesh refinement

Finite element modeling of charged species transport has enabled the ana...

0 Sungu Kim, et al. ∙

research

∙ 11/07/2022

Neural PDE Solvers for Irregular Domains

Neural network-based approaches for solving partial differential equatio...

0 Biswajit Khara, et al. ∙

research

∙ 09/27/2022

CyRSoXS: A GPU-accelerated virtual instrument for Polarized Resonant Soft X-ray Scattering (P-RSoXS)

Polarized Resonant Soft X-ray scattering (P-RSoXS) has emerged as a powe...

0 Kumar Saurabh, et al. ∙

research

∙ 09/25/2022

Scalable adaptive algorithms for next-generation multiphase simulations

The accuracy of multiphysics simulations is strongly contingent up on th...

0 Kumar Saurabh, et al. ∙

research

∙ 03/29/2022

Stochastic Conservative Contextual Linear Bandits

Many physical systems have underlying safety considerations that require...

0 Jiabin Lin, et al. ∙

research

∙ 11/17/2021

Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources

Complex flow simulations are conventionally performed on HPC clusters. H...

0 Kumar Saurabh, et al. ∙

research

∙ 10/04/2021

NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs

We consider a mesh-based approach for training a neural network to produ...

11 Biswajit Khara, et al. ∙

research

∙ 10/04/2021

Differentiable Spline Approximations

The paradigm of differentiable programming has significantly enhanced th...

24 Minsu Cho, et al. ∙

research

∙ 08/08/2021

Scalable adaptive PDE solvers in arbitrary domains

Efficiently and accurately simulating partial differential equations (PD...

0 Kumar Saurabh, et al. ∙

research

∙ 07/11/2021

A projection-based, semi-implicit time-stepping approach for the Cahn-Hilliard Navier-Stokes equations on adaptive octree meshes

We present a projection-based framework for solving a thermodynamically-...

0 Makrand A Khanwale, et al. ∙

research

∙ 04/29/2021

Distributed Multigrid Neural Solvers on Megavoxel Domains

We consider the distributed training of large-scale neural networks that...

18 Aditya Balu, et al. ∙

research

∙ 11/13/2020

Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications

Reliable seed yield estimation is an indispensable step in plant breedin...

1 Luis G Riera, et al. ∙

research

∙ 10/17/2020

Modeling electrochemical systems with weakly imposed Dirichlet boundary conditions

Finite element modeling of charged species transport has enabled analysi...

0 Sungu Kim, et al. ∙

research

∙ 09/13/2020

A fully-coupled framework for solving Cahn-Hilliard Navier-Stokes equations: Second-order, energy-stable numerical methods on adaptive octree based meshes

We present a fully-coupled, implicit-in-time framework for solving a the...

0 Makrand A Khanwale, et al. ∙

research

∙ 08/28/2020

Industrial scale large eddy simulations (LES) with adaptive octree meshes using immersogeometric analysis

We present a variant of the immersed boundary method integrated with oct...

0 Kumar Saurabh, et al. ∙

research

∙ 07/24/2020

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models

Recent progress in scientific machine learning (SciML) has opened up the...

14 Sergio Botelho, et al. ∙

research

∙ 06/24/2020

Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

Accurate prediction of crop yield supported by scientific and domain-rel...

17 Johnathon Shook, et al. ∙

research

∙ 06/07/2020

How useful is Active Learning for Image-based Plant Phenotyping?

Deep learning models have been successfully deployed for a diverse array...

57 Koushik Nagasubramanian, et al. ∙

research

∙ 12/28/2019

Simulating two-phase flows with thermodynamically consistent energy stable Cahn-Hilliard Navier-Stokes equations on parallel adaptive octree based meshes

We report on simulations of two-phase flows with deforming interfaces at...

0 Makrand A Khanwale, et al. ∙

research

∙ 06/04/2019

Encoding Invariances in Deep Generative Models

Reliable training of generative adversarial networks (GANs) typically re...

5 Ameya Joshi, et al. ∙

research

∙ 11/29/2018

Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning

Microfluidic devices are utilized to control and direct flow behavior in...

10 Xian Yeow Lee, et al. ∙

research

∙ 11/21/2018

Physics-aware Deep Generative Models for Creating Synthetic Microstructures

A key problem in computational material science deals with understanding...

0 Rahul Singh, et al. ∙

research

∙ 09/12/2018

PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization

PARyOpt is a python based implementation of the Bayesian optimization ro...

0 Balaji Sesha Sarath Pokuri, et al. ∙

research

∙ 05/30/2018

Predicting County Level Corn Yields Using Deep Long Short Term Memory Models

Corn yield prediction is beneficial as it provides valuable information ...

0 Zehui Jiang, et al. ∙

research

∙ 04/24/2018

Explaining hyperspectral imaging based plant disease identification: 3D CNN and saliency maps

Our overarching goal is to develop an accurate and explainable model for...

0 Koushik Nagasubramanian, et al. ∙

research

∙ 10/24/2017

Interpretable Deep Learning applied to Plant Stress Phenotyping

Availability of an explainable deep learning model that can be applied t...

0 Sambuddha Ghosal, et al. ∙

research

∙ 10/12/2017

Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean

Charcoal rot is a fungal disease that thrives in warm dry conditions and...

0 Koushik Nagasubramanian, et al. ∙

research

∙ 08/17/2016

A Bayesian Network approach to County-Level Corn Yield Prediction using historical data and expert knowledge

Crop yield forecasting is the methodology of predicting crop yields prio...

0 Vikas Chawla, et al. ∙

research

∙ 05/17/2016

Deep Action Sequence Learning for Causal Shape Transformation

Deep learning became the method of choice in recent year for solving a w...

0 Kin Gwn Lore, et al. ∙

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