Yannic Maus

Achieving a \(O(\log \log n)\) round complexity for computing 2-ruling sets in low-arboricity graphs could redefine efficiency benchmarks in distributed computing.

Achieving $O(\log n)$ approximation of APSP in constant rounds could revolutionize efficiency in multiparty computation settings.

Even approximately fair gift-giving is surprisingly hard in distributed systems: achieving any approximation for the Santa Claus problem requires $\Omega(\sqrt{n} + D)$ rounds.

Forget slow distributed algorithms: a new approach slashes the time to compute balanced orientations and degree splits by leveraging hypergraph sinkless orientations.

Distributed vertex coloring can now be solved in near-optimal $\tilde{O}(\log^4 \log n)$ rounds, closing the gap with the theoretical lower bound and exponentially improving performance for graphs with small maximum degree.