Publications
2022

Efficient Physics Informed Neural Networks Coupled with Domain Decomposition Methods for Solving Coupled Multiphysics Problems 2022 [URL]

Modeling, Analysis and Physics Informed Neural Network approaches for studying the dynamics of COVID19 involving humanhuman and humanpathogen interaction Computational and Mathematical Biophysics 2022 [URL]

Datadriven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks Letters in Biomathematics 2022 [URL]

ViscoelasticNet: A physics informed neural network framework for stress discovery and model selection arXiv preprint arXiv:2209.06972 2022 [URL]
2021

A physicsinformed deep learning framework for inversion and surrogate modeling in solid mechanics Computer Methods in Applied Mechanics and Engineering 2021 [URL]
2020

Systems biology informed deep learning for inferring parameters and hidden dynamics PLoS computational biology 2020 [URL]
2019

Machine Learning of Spacefractional Differential Equations SIAM Journal on Scientific Computing 2019 [URL]

On Parameter Estimation Approaches for Predicting Disease Transmission through Optimization, Deep Learning and Statistical Inference Methods Letters in Biomathematics 2019 [URL]

PhysicsInformed Neural Networks: A Deep Learning Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations Journal of Computational Physics 2019 [URL]
2018

ForwardBackward Stochastic Neural Networks: Deep Learning of Highdimensional Partial Differential Equations arXiv preprint arXiv:1804.07010 2018 [URL]

Multistep Neural Networks for Datadriven Discovery of Nonlinear Dynamical Systems arXiv preprint arXiv:1801.01236 2018 [URL]

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations Journal of Machine Learning Research 2018 [URL]

Numerical Gaussian Processes for TimeDependent and Nonlinear Partial Differential Equations SIAM Journal on Scientific Computing 2018 [URL]

Application of Local Improvements to Reducedorder Models to Sampling Methods for Nonlinear PDEs with Noise International Journal of Computer Mathematics 2018 [URL]
2017

Machine Learning of Linear Differential Equations using Gaussian Processes Journal of Computational Physics 2017 [URL]

Inferring Solutions of Differential Equations using Noisy Multifidelity Data Journal of Computational Physics 2017 [URL]

Nonlinear Information Fusion Algorithms for Dataefficient Multifidelity Modelling Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 2017 [URL]
2016
2014

The Differential Effects of Oil Demand and Supply Shocks on the Global Economy Energy Economics 2014 [URL]

A Multifidelity Stochastic Collocation Method for Parabolic Partial Differential Equations with Random Input Data International Journal for Uncertainty Quantification 2014 [URL]