Projects

Graph Neural Network for Finite Element Analysis

• Built a Graph Neural Network (GNN)-based surrogate model to accelerate parameter search in Finite Element Analysis (FEA).
• Achieved 99.3% accuracy on simulation data, enabling faster exploration of pressure and temperature parameters.

Link Prediction in Citation Networks

• Predicted missing edges in citation networks using Graph Neural Networks (GNNs) and semantic information.
• Ranked 2nd on Kaggle for this project.