Research output
Peer-reviewed papers, preprints, and public technical reports.
Zijie Li, Saurabh Patil, Francis Ogoke, Dule Shu, Wilson Zhen, Michael Schneier, John R. Buchanan Jr., and Amir Barati Farimani
A reduced-order modelling framework that learns system dynamics in a mesh-reduced latent space using a nonlinear autoencoder and a temporal prediction model.
Zijie Li, Anthony Zhou, Saurabh Patil, and Amir Barati Farimani
A factorized-attention model for global weather forecasting on spherical geometries, designed to reduce the computational cost of attention at global scales.
Saurabh Patil, Zijie Li, and Amir Barati Farimani
Introduces a neural operator based on Hyena's long convolutions and multiplicative gating, and evaluates it on diffusion–reaction and Navier–Stokes equations.
Zijie Li, Saurabh Patil, Dule Shu, and Amir Barati Farimani
Learns time-dependent PDE dynamics in a compressed latent space by first reducing the full-order representation and then predicting future states in that space.
Saurabh Patil, Parisa Mollaei, and Amir Barati Farimani
A transformer-based time-series forecasting study of new COVID-19 cases in India, Russia, and Brazil.
Hemant Kumar Sharma, Saurabh Patil, and Akshay Antony
An investigation of adversarial attacks on PointNet and DGCNN for 3D point-cloud classification using the ModelNet40 dataset.