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- Stefano Boccaletti

Discipline name
D-index
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Citations
Publications
World Ranking
National Ranking

Engineering and Technology
D-index
57
Citations
23,142
216
World Ranking
818
National Ranking
18

2016 - Member of Academia Europaea

- Quantum mechanics
- Statistics
- Artificial intelligence

His primary areas of investigation include Complex network, Synchronization, Topology, Synchronization of chaos and Statistical physics. His studies deal with areas such as Artificial neural network, Complex system, Neuroscience and Data mining as well as Complex network. His Topology research includes elements of Synchronization, Master stability function and Dynamical systems theory.

His Dynamical systems theory research is multidisciplinary, incorporating elements of Theoretical computer science, Laplacian matrix, Two-dimensional space, Scale and Scale-free network. His Scale-free network study deals with Network dynamics intersecting with Interdependent networks. His study in Synchronization of chaos is interdisciplinary in nature, drawing from both Chaotic, Chaotic systems and Phase synchronization.

- Complex networks: Structure and dynamics (7818 citations)
- The synchronization of chaotic systems (1949 citations)
- The structure and dynamics of multilayer networks. (1914 citations)

Stefano Boccaletti spends much of his time researching Complex network, Topology, Synchronization, Statistical physics and Control theory. His studies deal with areas such as Theoretical computer science, Distributed computing, Data mining, Representation and Complex system as well as Complex network. The Topology study which covers Synchronization that intersects with Oscillation.

His Synchronization studies intersect with other disciplines such as Explosive material and Dynamical systems theory. His biological study deals with issues like Phase, which deal with fields such as State and Amplitude. His study in Control theory is interdisciplinary in nature, drawing from both Synchronization of chaos, Control of chaos and Chaotic.

- Complex network (27.49%)
- Topology (24.80%)
- Synchronization (20.75%)

- Topology (24.80%)
- Complex network (27.49%)
- Synchronization (20.75%)

His main research concerns Topology, Complex network, Synchronization, Statistical physics and Synchronization. His Topology research is multidisciplinary, incorporating elements of Network topology, Mechanism and Relay. Stefano Boccaletti interconnects Complex system, Percolation, Nonlinear system, Node and Variety in the investigation of issues within Complex network.

His research on Statistical physics also deals with topics like

- Kuramoto model that connect with fields like Flocking, Coherent states, Coupling strength and Coupling,
- Pairwise comparison which is related to area like Theoretical computer science,
- Physical system which is related to area like Counterintuitive. His Synchronization research is multidisciplinary, relying on both Range, Real-time computing, Oscillation and Control theory. His Dynamical systems theory study combines topics in areas such as Interdependent networks and Master stability function.

- Statistical physics of human cooperation (632 citations)
- Punishment diminishes the benefits of network reciprocity in social dilemma experiments. (152 citations)
- Explosive transitions in complex networks’ structure and dynamics: Percolation and synchronization (145 citations)

- Quantum mechanics
- Statistics
- Artificial intelligence

His scientific interests lie mostly in Complex network, Topology, Synchronization, Synchronization and Interdependent networks. Stefano Boccaletti has included themes like Complex system, Fractal analysis and Nonlinear system in his Complex network study. Synchronization is intertwined with Dynamical systems theory, Theoretical computer science and Structure in his research.

His research investigates the connection between Dynamical systems theory and topics such as State that intersect with problems in Stability, Phenomenology and Master stability function. His study explores the link between Theoretical computer science and topics such as Simple that cross with problems in Prisoner's dilemma. His Interdependent networks study combines topics from a wide range of disciplines, such as Representation, Microeconomics and Distributed computing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Complex networks: Structure and dynamics

S. Boccaletti;V. Latora;V. Latora;Y. Moreno;M. Chavez.

Physics Reports **(2006)**

10442 Citations

The synchronization of chaotic systems

S. Boccaletti;J. Kurths;G. Osipov;D.L. Valladares.

Physics Reports **(2002)**

2802 Citations

The structure and dynamics of multilayer networks.

S. Boccaletti;G. Bianconi;R. Criado;R. Criado;C.I. del Genio.

Physics Reports **(2014)**

2397 Citations

The control of chaos: theory and applications

S. Boccaletti;C. Grebogi;Ying-Cheng Lai;H. Mancini.

Physics Reports **(2000)**

1061 Citations

Statistical physics of human cooperation

Matjaž Perc;Jillian J. Jordan;David G. Rand;Zhen Wang.

Physics Reports **(2017)**

684 Citations

Synchronization is Enhanced in Weighted Complex Networks

M. Chavez;D.-U. Hwang;A. Amann;H. G. E. Hentschel.

Physical Review Letters **(2005)**

500 Citations

Emergence of network features from multiplexity

Alessio Cardillo;Jesús Gómez-Gardeñes;Massimiliano Zanin;Massimiliano Zanin;Miguel Romance;Miguel Romance.

Scientific Reports **(2013)**

452 Citations

PATTERN FORMATION AND COMPETITION IN NONLINEAR OPTICS

F.Tito Arecchi;Stefano Boccaletti;PierLuigi Ramazza.

Physics Reports **(1999)**

353 Citations

Detecting complex network modularity by dynamical clustering

S. Boccaletti;M. Ivanchenko;V. Latora;A. Pluchino.

Physical Review E **(2007)**

252 Citations

Characterization of intermittent lag synchronization

S Boccaletti;DL Valladares;DL Valladares.

Physical Review E **(2000)**

239 Citations

Chaos, Solitons and Fractals

(Impact Factor: 9.922)

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Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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