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About

Pietro De Lellis is a leading figure in the study of complex networked systems, with a research portfolio that bridges control theory, collective behavior, and bio-robotics. His work focuses on understanding and controlling synchronization, formation, and fragmentation in multi-agent systems—from robot swarms to animal groups. De Lellis made a foundational contribution with his 2010 work on synchronization and control of complex networks (145 citations), which introduced contraction and adaptation frameworks for networked dynamics. He has since advanced the field through innovative applications: using machine learning to classify collective behavior across animal species (57 citations), developing decentralized formation control for stochastic multi-vehicle systems (33 citations), and analyzing group fragmentation through topological methods (24 citations). Notably, his 2021 study on spontaneous leadership patterns in human networks (21 citations) and his model-based feedback control of live zebrafish via robotic replicas (17 citations) demonstrate his unique ability to merge theory with experimental validation. De Lellis’s work on formation control for non-holonomic robots on slippery surfaces and pause-and-go self-balancing algorithms further showcases his practical engineering impact. His research has been widely cited, reflecting its influence across control engineering, robotics, and ethology.