Dana Randall

55 papers receiving 667 citations

Peers

Dana Randall
Comparison fields: 5 of 85
  • Statistics and Probability 340
  • Mathematical Physics 261
  • Discrete Mathematics and Combinatorics 71
  • Condensed Matter Physics 127
  • Computational Theory and Mathematics 162
Replace Alexander E. Holroyd with:
Alexander E. Holroyd United States
Jeffrey E. Steif Sweden
Gady Kozma Israel
Guy Louchard Belgium
Eyal Lubetzky United States
Daniel Štefankovič United States
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Catherine Greenhill Australia
Louigi Addario‐Berry Canada
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Citations per year

Countries citing papers authored by Dana Randall

Since Specialization
Citations

This map shows the geographic impact of Dana Randall's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dana Randall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana Randall more than expected).

Fields of papers citing papers by Dana Randall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dana Randall. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dana Randall. The network helps show where Dana Randall may publish in the future.

Co-authors

The 25 scholars most cited alongside Dana Randall, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dana Randall Line = papers co-authored together Dana Randall links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200176
2 200074
3 200171
4 200245
5 199642
6 200630
7 200228
8 200227
9 200424
10 202322
11
Sampling spin configurations of an Ising system
199918
12 199218
13
Markov Chain Algorithms for Planar Lattice Structures (Extended Abstract)
199515
14 200614
15
Counting triangulations and pseudo-triangulations of wheels.
200113
16
Sampling stable marriages: why spouse-swapping won't work
200813
17 199312
18 199911
19 200610
20 20089

About Dana Randall

Dana Randall is a scholar working on Statistics and Probability, Mathematical Physics, Artificial Intelligence, Condensed Matter Physics and Computational Theory and Mathematics, having authored 58 papers that have together received 725 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (34 papers), Stochastic processes and statistical mechanics (31 papers), Theoretical and Computational Physics (10 papers), Bayesian Methods and Mixture Models (7 papers), Point processes and geometric inequalities (6 papers), Advanced Combinatorial Mathematics (6 papers), Mass Spectrometry Techniques and Applications (4 papers) and Bayesian Modeling and Causal Inference (4 papers). The work is most often cited by research in Statistics and Probability (340 citations), Mathematical Physics (261 citations), Discrete Mathematics and Combinatorics (71 citations), Condensed Matter Physics (127 citations) and Computational Theory and Mathematics (162 citations). Dana Randall has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Alistair Sinclair, Michael Luby, Claire Kenyon, Prasad Tetali, Neal Madras, Anna R. Karlin, Russell Martin, Cristopher Moore, Peter G. Doyle and Mary Cryan. Their work appears in journals such as SIAM Journal on Discrete Mathematics, Random Structures and Algorithms, Algorithmica, Theoretical Computer Science and Combinatorics Probability Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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