Rasmus Kyng earned his PhD in Computer Science from Yale University in summer 2017. His advisor was Daniel Spielman. Before attending Yale, Kyng received a BA in Computer Science from the University of Cambridge in 2011. Kyng's research is focused on fast graph algorithms and their applications to machine learning. His work often relies on randomized numerical linear algebra.
- Bridging Continuous and Discrete Optimization, Fall 2017. Research Fellow and Workshop Organizer.