Rasmus Kyng

Rasmus Kyng is an Associate Professor in the Department of Computer Science at ETH Zurich. His research interests include algorithms, convex optimization, graph algorithms, numerical linear algebra, fine-grained complexity theory, and random matrix theory. Prof. Kyng's work focuses on advancing theoretical and applied computational methods within these areas. His profile page provides additional details about his academic and research activities.

Rasmus Kyng is a researcher at ETH Zurich specializing in algorithms for solving large-scale linear systems and network flow problems. His work focuses on developing efficient algorithms for problems such as minimum-cost flow, Laplacian systems, and isotonic regression. Kyng's research emphasizes the design of nearly-linear time algorithms, often leveraging techniques like sparsification, preconditioning, and iterative refinement. His contributions include significant advances in solving directed Laplacian systems, incremental and decremental graph algorithms, and robust methods for solving structured linear systems. His work has applications in optimization, machine learning, and data analysis.