Demo Data from EDBT 2026 / reviewers in the wild / expert
Richard Elwes
dblp:09/1993
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2014
0000-0002-6752-5501ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 28% Information theory · 28% Computational complexity · 28% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithmic game theory and mechanism design › network games
schelling segregation model |
0.2 | 1 | 2014 | Digital Morphogenesis via Schelling Segregation · FOCS 2014 |
Information theory › probability theory
threshold phenomena |
0.2 | 1 | 2014 | Digital Morphogenesis via Schelling Segregation · FOCS 2014 |
Combinatorics and discrete mathematics › statistical physics models
ising model |
0.1 | 1 | 2014 | Digital Morphogenesis via Schelling Segregation · FOCS 2014 |
Combinatorics and discrete mathematics
statistical physics models |
0.1 | 1 | 2014 | Digital Morphogenesis via Schelling Segregation · FOCS 2014 |
Methods — techniques the papers use, named apart from their topics
stochastic evolutionary game theory · 0.2statistical mechanics · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Digital Morphogenesis via Schelling SegregationabstractSchelling's model of segregation looks to explain the way in which particles or agents of two types may come to arrange themselves spatially into configurations consisting of large homogeneous clusters, i.e. connected regions consisting of only one type. As one of the earliest agent based models studied by economists and perhaps the most famous model of self-organising behaviour, it also has direct links to areas at the interface between computer science and statistical mechanics, such as the Ising model and the study of contagion and cascading phenomena in networks. While the model has been extensively studied it has largely resisted rigorous analysis, prior results from the literature generally pertaining to variants of the model which are tweaked so as to be amenable to standard techniques from statistical mechanics or stochastic evolutionary game theory. In BK, Brandt, Immorlica, Kamath and Kleinberg provided the first rigorous analysis of the unperturbed model, for a specific set of input parameters. Here we provide a rigorous analysis of the model's behaviour much more generally and establish some surprising forms of threshold behaviour, notably the existence of situations where an increased level of intolerance for neighbouring agents of opposite type leads almost certainly to decreased segregation. George Barmpalias, Richard Elwes, Andy Lewis-Pye |
FOCS | 2 |
| 2007 | Asymptotic classes of finite structuresabstractIn this paper we consider classes of finite structures where we have good control over the sizes of the definable sets. The motivating example is the class of finite fields: it was shown in [1] that for any formula in the language of rings, there are finitely many pairs (d,μ) ∈ω×Q>0so that in any finite fieldFand for any ā ∈Fmthe size |ø(Fn,ā)| is “approximately”μ|F|d. Essentially this is a generalisation of the classical Lang-Weil estimates from the category of varieties to that of the first-order-definable sets. Richard Elwes |
J. Symb. Log. | 1 |