If you are experiencing poor outcomes, confusing errors, or training difficulties while using Graph Neural Networks (GNNs), I can offer assistance.

As a doctoral candidate specializing in Graph Neural Networks with over six years of practical experience in AI/ML, I am available to help.

My services include:

• Debugging models built with PyTorch Geometric or DGL
• Reviewing your GNN structure and programming
• Resolving training problems or performance limitations
• Developing new GNN models (such as GCN, GAT, GraphSAGE, GIN, and others)
• Providing support for temporal, heterogeneous, or multi-relational graphs
• Offering guidance on creating graphs from unprocessed or tabular information
• Providing PDF summaries and suggestions for training upon request

Regardless of whether you are a researcher, student, or developer, I will help ensure your model operates correctly and achieves improved performance.

Select the option that suits your requirements, and please reach out to me before placing an order!