What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Statistics
- Combinatorics
Remco van der Hofstad mainly focuses on Combinatorics, Random graph, Discrete mathematics, Exponent and Statistical physics.
His work deals with themes such as Critical exponent, Central limit theorem, Random variable and Self-avoiding walk, which intersect with Combinatorics.
His Random graph research incorporates elements of Theoretical computer science, Degree, Degree distribution, Graph theory and Convergence of random variables.
His Theoretical computer science research focuses on subjects like Complex network, which are linked to Probabilistic logic.
His Discrete mathematics study integrates concerns from other disciplines, such as Phase transition, Upper and lower bounds and Distance.
His studies deal with areas such as Motion, Percolation, Function, Moment and Scale-free network as well as Statistical physics.
His most cited work include:
- Random Graphs and Complex Networks (521 citations)
- Random Graphs and Complex Networks: Volume 1 (131 citations)
- Probing exchange pathways in one-dimensional aggregates with super-resolution microscopy (125 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Combinatorics, Random graph, Discrete mathematics, Exponent and Percolation.
The study incorporates disciplines such as Upper and lower bounds, Random walk and Random variable in addition to Combinatorics.
Remco van der Hofstad combines subjects such as Degree, Degree distribution, Statistical physics, First passage percolation and Scaling with his study of Random graph.
He has researched Scaling in several fields, including Phase transition and Brownian motion.
His Discrete mathematics study which covers Lattice that intersects with Critical dimension.
His Percolation study combines topics from a wide range of disciplines, such as Function, Dimension, Critical exponent and Cluster.
He most often published in these fields:
- Combinatorics (52.66%)
- Random graph (46.39%)
- Discrete mathematics (35.42%)
What were the highlights of his more recent work (between 2018-2021)?
- Random graph (46.39%)
- Discrete mathematics (35.42%)
- Combinatorics (52.66%)
In recent papers he was focusing on the following fields of study:
His main research concerns Random graph, Discrete mathematics, Combinatorics, Statistical physics and Exponent.
His Random graph research includes themes of Preferential attachment, Multiplicative function, Degree, Degree distribution and Upper and lower bounds.
His biological study spans a wide range of topics, including Multiple edges, Clustering coefficient and Scaling.
His Discrete mathematics research is multidisciplinary, incorporating perspectives in Graph, Mixing, Null hypothesis, Asymptotically optimal algorithm and Random walk.
The various areas that he examines in his Combinatorics study include Branching random walk and Scaling limit.
His Statistical physics research is multidisciplinary, relying on both Metric space and Extreme value theory.
Between 2018 and 2021, his most popular works were:
- Scale-free networks well done (64 citations)
- Lace Expansion and Mean-Field Behavior for the Random Connection Model (11 citations)
- Scale-free network clustering in hyperbolic and other random graphs (9 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Statistics
- Combinatorics
His scientific interests lie mostly in Random graph, Discrete mathematics, Combinatorics, Preferential attachment and Statistical physics.
His work carried out in the field of Random graph brings together such families of science as Random variable, Multiplicative function, Renormalization group, Degree and Universality.
He connects Discrete mathematics with Exponent in his research.
The concepts of his Combinatorics study are interwoven with issues in Trichotomy and Backtracking.
His Statistical physics study incorporates themes from Estimator, Mathematical proof, Network science and Extreme value theory.
Remco van der Hofstad interconnects Lévy process and Scaling in the investigation of issues within Degree distribution.
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