BARC talk by Marek Sokołowski

Tuesday, May 5, 2026, 13:00-14:00, Marek Sokołowski, Postdoc at the Max Planck Institute in Saarbrücken, Germany, will be giving a BARC talk on "Strongly Polynomial Parallel Work-Depth Tradeoffs for Directed SSSP".

Abstract:
We show new strongly polynomial work-depth tradeoffs for computing single-source shortest paths (SSSP) in non-negatively weighted directed graphs in parallel. Most importantly, we prove that directed SSSP can be solved within Õ(m + n^{2-ε}) work and Õ(m + n^{1-ε}) depth for some positive ε>0. In particular, for dense graphs with non-negative real weights, we provide the first nearly work-efficient strongly polynomial algorithm with sublinear depth.

Our result immediately yields improved strongly polynomial parallel algorithms for min-cost flow and the assignment problem. It also leads to the first non-trivial strongly polynomial dynamic algorithm for minimum mean cycle. Moreover, we develop efficient parallel algorithms in the Word RAM model for several variants of SSSP in graphs with exponentially large edge weights.

Based on a joint work with Wojciech Nadara and Adam Karczmarz (University of Warsaw), presented at SODA’26.

Bio:
Marek Sokołowski is a postdoctoral researcher, working at the Algorithms and Complexity group in the Max Planck Institute for Informatics in Saarbrücken, Germany. He wrote his PhD thesis at the University of Warsaw under the supervision of Michał Pilipczuk. His research interests include graph theory (with focus on algorithms and dynamic algorithms on graphs) and parameterized algorithms (with particular affinity to graph width parameters and parameterized data structures).

Host:
Tuukka Korhonen