معرفی
Rasmus Kyng is an Assistant Professor in the Department of Computer Science at ETH Zurich, where he has been since 2019. His research focuses on fast algorithms for graph problems, convex optimization, and their applications in machine learning. He has received grants from the Swiss National Science Foundation, including project grants and a starting grant.
Education: B.A. in Computer Science from the University of Cambridge (2011), PhD in Computer Science from Yale University (2017), advised by Daniel A. Spielman. Postdoctoral positions included Harvard University (2018–2019) and a research fellowship at the Simons Institute, UC Berkeley (2017).
Research Interests: Development of nearly linear-time algorithms for fundamental graph problems (e.g., maximum flow, minimum-cost flow), dynamic graph algorithms, discrepancy theory, and fine-grained complexity. His work bridges numerical linear algebra and combinatorial optimization, emphasizing practical implementations such as the Laplacians.jl package.
Awards: FOCS Best Paper Award (2022), Inaugural ICBS Frontiers of Science Award (2022), Machtey Award (Best Student Paper, FOCS 2017).
Teaching: Advanced Graph Algorithms and Optimization (ETH Zurich, 2020–2023), Algorithms, Probability, and Computing (ETH Zurich, 2020–2022). Supervised numerous PhD students and mentored postdocs in theoretical computer science.
Labs/Teams: Co-leads a research group with Maximilian Probst Gutenberg, focusing on dynamic graph algorithms and optimization. Collaborations include work on sparsification, spectral graph theory, and machine learning applications.
