What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- The Internet
Alain Barrat mostly deals with Theoretical computer science, Complex network, Evolving networks, Statistical physics and Face-to-face.
His Theoretical computer science research includes themes of Network topology, Structure, The Internet and Communications system.
His studies link Data science with Complex network.
His work carried out in the field of Data science brings together such families of science as Causal structure and Network data.
The concepts of his Statistical physics study are interwoven with issues in Discrete mathematics and Degree.
His study in Public health is interdisciplinary in nature, drawing from both Developmental psychology and Isolation.
His most cited work include:
- The architecture of complex weighted networks (2732 citations)
- Dynamical Processes on Complex Networks (1271 citations)
- The role of the airline transportation network in the prediction and predictability of global epidemics (860 citations)
What are the main themes of his work throughout his whole career to date?
Alain Barrat spends much of his time researching Statistical physics, Complex network, Theoretical computer science, Data mining and Data science.
His work on Statistical mechanics as part of general Statistical physics research is frequently linked to Focus, bridging the gap between disciplines.
His study looks at the relationship between Complex network and topics such as Complex system, which overlap with Pairwise comparison.
His studies deal with areas such as Evolving networks, Structure, Centrality and The Internet as well as Theoretical computer science.
As part of the same scientific family, Alain Barrat usually focuses on Data mining, concentrating on Computational model and intersecting with Dynamic network analysis and Raw data.
Alain Barrat has included themes like Data collection and Social network in his Data science study.
He most often published in these fields:
- Statistical physics (27.38%)
- Complex network (29.39%)
- Theoretical computer science (22.77%)
What were the highlights of his more recent work (between 2016-2021)?
- Theoretical computer science (22.77%)
- Data mining (25.36%)
- Social network (11.53%)
In recent papers he was focusing on the following fields of study:
His main research concerns Theoretical computer science, Data mining, Social network, Social group and Contact tracing.
The various areas that he examines in his Theoretical computer science study include Centrality, Relevance and Group cohesiveness.
His Data mining research incorporates themes from Surrogate data, Probability distribution, Universality and Complex network.
The Complex network study combines topics in areas such as Simplicial complex, Pairwise comparison and Emotional contagion.
His Social network study combines topics in areas such as Data science and Computational sociology.
In his study, Weighted network is strongly linked to Structure, which falls under the umbrella field of Social group.
Between 2016 and 2021, his most popular works were:
- Simplicial models of social contagion (128 citations)
- Simplicial models of social contagion (128 citations)
- Decentralized Privacy-Preserving Proximity Tracing (80 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Topology
Alain Barrat mostly deals with Complex network, Theoretical computer science, Econometrics, Null model and Complex system.
His work in Complex network is not limited to one particular discipline; it also encompasses Social group.
His biological study spans a wide range of topics, including Centrality, Relevance, Graph and Group cohesiveness.
His research integrates issues of Interpersonal ties, Structure and Set in his study of Null model.
His Complex system research includes elements of Simplicial complex, Statistical physics, Pairwise comparison and Discontinuous transition.
His Pairwise comparison research is multidisciplinary, incorporating perspectives in Outcome, Network model, Emotional contagion and Social system.
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.
