21 citations · 38 across the 5 of their papers we have counts for
5 papers
Reinforcement learning framework for the mechanical design of microelectronic components under multiphysics constraints
Siddharth Nair, Timothy F. Walsh, Greg Pickrell +1
This study focuses on the development of reinforcement learning based techniques for the design of microelectronic components under multiphysics constraints. While traditional desi…
Time transient Simulations via Finite Element Network Analysis: Theoretical Formulation and Numerical Validation
Mehdi Jokar, Siddharth Nair, Fabio Semperlotti
This paper extends the finite element network analysis (FENA) to include a dynamic time-transient formulation. FENA was initially formulated in the context of the linear static ana…
Physics and geometry informed neural operator network with application to acoustic scattering
Siddharth Nair, Timothy F. Walsh, Greg Pickrell +1
In this paper, we introduce a physics and geometry informed neural operator network with application to the forward simulation of acoustic scattering. The development of geometry i…
Multiple scattering simulation via physics-informed neural networks
Siddharth Nair, Timothy F. Walsh, Greg Pickrell +1
This work presents a physics-driven machine learning framework for the simulation of acoustic scattering problems. The proposed framework relies on a physics-informed neural networ…
GRIDS-Net: Inverse shape design and identification of scatterers via geometric regularization and physics-embedded deep learning
Siddharth Nair, Timothy F. Walsh, Greg Pickrell +1
This study presents a deep learning based methodology for both remote sensing and design of acoustic scatterers. The ability to determine the shape of a scatterer, either in the co…