What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Statistics
- Mathematical analysis
Ginestra Bianconi mainly focuses on Complex network, Complex system, Statistical physics, Theoretical computer science and Degree distribution.
Ginestra Bianconi interconnects Centrality, Curse of dimensionality, Quantum gravity, Entropy and Topology in the investigation of issues within Complex network.
His Complex system research includes elements of Multiplex, Network theory, Structure, Node and Data science.
Ginestra Bianconi combines subjects such as Discrete mathematics, Network topology and Degree with his study of Statistical physics.
His biological study spans a wide range of topics, including Cover, Node, Inference, Evolving networks and Biological network.
In his work, Tetrahedron is strongly intertwined with Pure mathematics, which is a subfield of Degree distribution.
His most cited work include:
- The structure and dynamics of multilayer networks. (1914 citations)
- Competition and multiscaling in evolving networks (770 citations)
- Theory of rumour spreading in complex social networks (514 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Statistical physics, Complex network, Topology, Phase transition and Complex system.
His work deals with themes such as Function, Network dynamics, Percolation and Random graph, which intersect with Statistical physics.
His Complex network research includes themes of Network topology, Information theory and Theoretical computer science.
The various areas that he examines in his Theoretical computer science study include Space and Biological network.
His Topology research incorporates themes from Node, Multiplex and Interdependent networks, Robustness.
His Complex system research incorporates elements of Simplicial complex, Pure mathematics, Network model, Network theory and Structure.
He most often published in these fields:
- Statistical physics (29.07%)
- Complex network (27.34%)
- Topology (19.38%)
What were the highlights of his more recent work (between 2018-2021)?
- Topology (19.38%)
- Pure mathematics (8.30%)
- Statistical physics (29.07%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Topology, Pure mathematics, Statistical physics, Complex network and Topology.
He interconnects Network topology, Multiplex, Network science and Robustness in the investigation of issues within Topology.
His Pure mathematics research includes elements of Renormalization group and Order.
His Statistical physics research includes themes of Range, Phase transition and Function.
His research integrates issues of Theoretical computer science, Principle of maximum entropy, Distribution, Information theory and Space in his study of Complex network.
Ginestra Bianconi has researched Topology in several fields, including Clique, Node, Complex system, Betti number and Clustering coefficient.
Between 2018 and 2021, his most popular works were:
- Explosive higher-order Kuramoto dynamics on simplicial complexes (42 citations)
- Synchronization in network geometries with finite spectral dimension. (33 citations)
- Beyond the clustering coefficient: A topological analysis of node neighbourhoods in complex networks (21 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Statistics
- Mathematical analysis
Ginestra Bianconi mostly deals with Renormalization group, Epidemic model, Statistics, Complex network and Complex system.
His study on Renormalization group also encompasses disciplines like
- Network dynamics and related Random graph, Mathematical physics and Spectral dimension,
- Universality which intersects with area such as Phase transition, Fractal, Probability and statistics and Farey sequence.
The study incorporates disciplines such as Clique and Topology in addition to Complex network.
His Topology research is multidisciplinary, incorporating perspectives in Node, Betti number, Clustering coefficient and Network science.
His Complex system study combines topics in areas such as Structure and Simplicial complex, Pure mathematics.
In his study, he carries out multidisciplinary Kuramoto model and Statistical physics research.
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