Linear Algebra

Linear algebra, the study of vectors, matrices, and linear transformations, underpins numerous scientific and engineering disciplines. Current research emphasizes its applications in machine learning, particularly focusing on efficient algorithms for large-scale problems and the development of novel architectures like graph neural networks (GNNs) to handle sparse matrices and complex data structures. This focus is driven by the need for faster and more efficient solutions in areas such as federated learning, preconditioner design for iterative solvers, and explainable AI, ultimately impacting the speed and accuracy of computations across diverse fields.