Scholar
Haosu Zhou
Google Scholar ID: QqzrCL8AAAAJ
Imperial College London
Machine learning
surrogate models
metal forming
solid mechanics
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Citations & Impact
All-time
Citations
214
H-index
7
i10-index
7
Publications
14
Co-authors
0
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Publications
5 items
Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming
2026
Cited
0
Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation
2026
Cited
0
StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping
2026
Cited
0
Recurrent U-Net-Based Graph Neural Network (RUGNN) for Accurate Deformation Predictions in Sheet Material Forming
2025
Cited
0
A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components
2025
Cited
0
Resume (English only)
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0 total
Co-authors: 0 (list not available)
