Graph Neural Networks

My recent research has focused on Graph Neural Networks (GNNs) for learning actionable representations of graph-structured data, which is commonly generated in scientific applications. My long-term goal is to develop robust data-driven decision making tools to augment and accelerate scientific discovery, e.g. the design of novel biomolecules and sustainable materials.

Towards developing the next generation of GNN architectures, I have open-sourced better benchmarks for modern GNNs which are enabling the community to explore their theoretical and empirical limitations. A good place to get started with GNNs would be my introductory blogposts on graph representation learning with GNNs and their connection with the popular Transformer model from NLP.

Chaitanya K. Joshi
Chaitanya K. Joshi
Research Engineer