Papers
1
Total Citations
11
H-Index
1
About
Haosen Cao is a researcher whose work illuminates the structural dynamics of complex systems. His primary focus lies in network science, particularly the analysis of large-scale hierarchical networks found in biological collectives, gene regulation, and engineered systems like multi-robot teams, unmanned vehicle swarms, and smart grids. Cao’s most cited paper, “The Immense Impact of Reverse Edges on Large Hierarchical Networks” (2023), has already garnered 11 citations, demonstrating its immediate relevance. In this work, he reveals how seemingly minor reverse edges can fundamentally alter the stability and flow of information within directed hierarchies—a finding with profound implications for designing resilient artificial networks. By bridging theoretical graph theory with practical engineering challenges, Cao provides critical insights for optimizing coordination in autonomous systems and infrastructure networks. His contributions are particularly valuable for researchers seeking to understand how subtle structural modifications can cascade through complex systems, making his work essential reading for those studying network robustness, swarm intelligence, and hierarchical control.
Research Focus
Key Achievements
Top Papers
- 1The Immense Impact of Reverse Edges on Large Hierarchical Networks11 citations · 2023