H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 31 Citations 7,977 130 World Ranking 7575 National Ranking 124


What is he best known for?

The fields of study he is best known for:

  • Computer network
  • The Internet
  • Statistics

The scientist’s investigation covers issues in Complex network, Graph theory, Discrete mathematics, Markov chain and Adjacency matrix. A large part of his Complex network studies is devoted to Small-world network. His Small-world network research incorporates elements of Modularity, Sociotechnical system, Complex contagion, Emotional contagion and Scale-free network.

Piet Van Mieghem combines subjects such as Topology, Theoretical computer science, Network dynamics and Graph with his study of Graph theory. He works mostly in the field of Discrete mathematics, limiting it down to concerns involving Degree and, occasionally, Tree, Random graph and Random regular graph. His Adjacency matrix research integrates issues from Complex system, Upper and lower bounds, Statistical physics and Markov process.

His most cited work include:

  • Epidemic processes in complex networks (1897 citations)
  • Virus spread in networks (763 citations)
  • Graph Spectra for Complex Networks (461 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Discrete mathematics, Combinatorics, Distributed computing, Complex network and Computer network. His work carried out in the field of Discrete mathematics brings together such families of science as Upper and lower bounds and Shortest path problem. His Distributed computing research is multidisciplinary, incorporating elements of Routing table, Network topology, Static routing, Node and Robustness.

His research in Static routing tackles topics such as Destination-Sequenced Distance Vector routing which are related to areas like Quality of service and Equal-cost multi-path routing. His research integrates issues of Algebraic connectivity, Theoretical computer science and Topology in his study of Complex network. He has researched Adjacency matrix in several fields, including Statistical physics and Markov process.

He most often published in these fields:

  • Discrete mathematics (17.83%)
  • Combinatorics (16.09%)
  • Distributed computing (14.78%)

What were the highlights of his more recent work (between 2018-2021)?

  • Epidemic model (6.09%)
  • Topology (10.43%)
  • Complex network (12.61%)

In recent papers he was focusing on the following fields of study:

Piet Van Mieghem mainly investigates Epidemic model, Topology, Complex network, Robustness and Adjacency matrix. His work carried out in the field of Topology brings together such families of science as Network topology, Voltage drop, Path graph and Complete graph. His studies deal with areas such as Data mining, Feature, Controllability, Network controllability and Community structure as well as Complex network.

His Robustness study integrates concerns from other disciplines, such as Network performance, Distributed computing and Connected component. His Adjacency matrix research is multidisciplinary, incorporating perspectives in Betweenness centrality, Statistical physics, Laplacian matrix and Spectral gap. His research investigates the link between Topology and topics such as Markov chain that cross with problems in Markov process.

Between 2018 and 2021, his most popular works were:

  • The simplex geometry of graphs (15 citations)
  • Mapping functional brain networks from the structural connectome : Relating the series expansion and eigenmode approaches (14 citations)
  • Network-inference-based prediction of the COVID-19 epidemic outbreak in the Chinese province Hubei (13 citations)

In his most recent research, the most cited papers focused on:

  • Computer network
  • The Internet
  • Statistics

Inference, Epidemic model, Applied mathematics, Statistical physics and Adjacency matrix are his primary areas of study. His Inference research includes elements of Almost surely and Algorithm, Computation, Prediction algorithms. His Applied mathematics research is multidisciplinary, relying on both State vector and Differential equation.

His Statistical physics study combines topics from a wide range of disciplines, such as Zero and Complex network. His Adjacency matrix research focuses on Functional magnetic resonance imaging and how it connects with State. His study in State is interdisciplinary in nature, drawing from both Linear system and Exponential stability, Stability.

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.

Top Publications

Epidemic processes in complex networks

Romualdo Pastor-Satorras;Claudio Castellano;Piet Van Mieghem;Alessandro Vespignani.
Reviews of Modern Physics (2015)

2223 Citations

Virus spread in networks

Piet Van Mieghem;Jasmina Omic;Robert Kooij.
IEEE ACM Transactions on Networking (2009)

940 Citations

Graph Spectra for Complex Networks

Piet Van Mieghem.

748 Citations

Performance Analysis of Communications Networks and Systems

Piet Van Mieghem.

360 Citations

Concepts of exact QoS routing algorithms

Piet Van Mieghem;Fernando A. Kuipers.
IEEE ACM Transactions on Networking (2004)

350 Citations

Hop-by-hop quality of service routing

Piet Van Mieghem;Hans De Neve;Fernando Kuipers.
Computer Networks (2001)

258 Citations

Generalized epidemic mean-field model for spreading processes over multilayer complex networks

Faryad Darabi Sahneh;Caterina Scoglio;Piet Van Mieghem.
IEEE ACM Transactions on Networking (2013)

240 Citations

The N -intertwined SIS epidemic network model

Piet Van Mieghem.
Computing (2011)

228 Citations

Theory of band tails in heavily doped semiconductors

Piet Van Mieghem.
Reviews of Modern Physics (1992)

214 Citations

Effect of the interconnected network structure on the epidemic threshold.

Huijuan Wang;Qian Li;Gregorio D'Agostino;Shlomo Havlin.
Physical Review E (2013)

182 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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