Rapid feasibility assessment of components formed through hot stamping: A deep learning approach. - Hamid Reza Attar; Haosu Zhou; Alistair Foster; Nan Li (CoRR, 2021)

Development of a deep learning platform for optimising sheet stamping geometries subject to manufacturing constraints. - Hamid Reza Attar; Alistair Foster; Nan Li (CoRR, 2022)

Development of a Deep Learning Platform for Sheet Stamping Geometry Optimisation under Manufacturing Constraints. - Hamid Reza Attar; Alistair Foster; Nan Li (Eng. Appl. Artif. Intell., 2023)

Implicit Neural Representations of Sheet Stamping Geometries with Small-Scale Features. - Hamid Reza Attar; Alistair Foster; Nan Li (Eng. Appl. Artif. Intell., 2023)

A review of graph neural network applications in mechanics-related domains. - Yingxue Zhao; Haoran Li; Haosu Zhou; Hamid Reza Attar; Tobias Pfaff; Nan Li (Artif. Intell. Rev., 2024)

Recurrent U-Net-Based Graph Neural Network (RUGNN) for Accurate Deformation Predictions in Sheet Material Forming. - Yingxue Zhao; Qianyi Chen; Haoran Li; Haosu Zhou; Hamid Reza Attar; Tobias Pfaff; Tailin Wu; Nan Li (CoRR, 2025)