Guiding students in Machine Learning through in-person and online assistance, providing clarifications on theory and applications.

At the Timely Approximations Group, led by Kartic Subr.Project description:Building a Graph Neural Network (GNN) to predict parameters for coarsening 3d meshes. This replaces optimising over the high-dimensional parameter space for each mesh separately.Personal learning outcomes:- Immersing myself in a previously unknown field, such as computational geometry and physics simulations- Studying various GNN architectures and their applications- Handling losses with unknown gradients- Gaining experience working in research

Radio frequency licensing specialist for Satellite-Ground communication