J. Laurie Snell
- Artificial Intelligence top 0.5%
- Computational Theory and Mathematics top 0.2%
- Statistical and Nonlinear Physics top 0.5%
- Statistics and Probability top 0.2%
- Computer Networks and Communications top 1%
- Co-authors
- John G. KemenyPeter G. DoyleRoss KindermannKeith BushAnthony W. KnappAleksandr I︠A︡kovlevich KhinchinGeorge C. RungerDavid Montgomery
- Topics
- Markov Chains and Monte Carlo Methods (9 papers)Stochastic processes and statistical mechanics (8 papers)Statistics Education and Methodologies (7 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
J. Laurie Snell
68 papers receiving 7.6k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Artificial Intelligence 1.8k
- Computational Theory and Mathematics 1.5k
- Statistical and Nonlinear Physics 1.2k
- Statistics and Probability 1.0k
- Computer Networks and Communications 981
Countries citing papers authored by J. Laurie Snell
This map shows the geographic impact of J. Laurie Snell'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 J. Laurie Snell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Laurie Snell more than expected).
Fields of papers citing papers by J. Laurie Snell
This network shows the impact of papers produced by J. Laurie Snell. 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 J. Laurie Snell. The network helps show where J. Laurie Snell may publish in the future.
Co-authorship network of co-authors of J. Laurie Snell
This figure shows the co-authorship network connecting the top 25 collaborators of J. Laurie Snell. A scholar is included among the top collaborators of J. Laurie Snell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with J. Laurie Snell. J. Laurie Snell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 17 | |
| 5 | Random Walks and Electric Networksbreakdown → | 1063 |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 12 | |
| 11 | 34 | |
| 12 | 6 | |
| 13 | 5 | |
| 14 | 9 | |
| 15 | 13 | |
| 16 | 50 | |
| 17 | Mathematical Foundations of Information Theory.breakdown → | 881 |
| 18 | 11 | |
| 19 | 222 | |
| 20 | 90 |
About J. Laurie Snell
J. Laurie Snell is a scholar working on Statistics and Probability, Mathematical Physics and Theoretical Computer Science, having authored 77 papers that have together received 8.5k indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (9 papers), Stochastic processes and statistical mechanics (8 papers) and Statistics Education and Methodologies (7 papers). The work is most often cited by research in Statistics and Probability (1.0k citations), Mathematical Physics (901 citations) and Computational Theory and Mathematics (1.5k citations). J. Laurie Snell has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include John G. Kemeny, Peter G. Doyle, Ross Kindermann, Keith Bush, Anthony W. Knapp, Aleksandr I︠A︡kovlevich Khinchin, George C. Runger, David Montgomery, Sir Ronald A. Fisher and A. A. Walters. Their work appears in journals such as Journal of the American Statistical Association, Econometrica and American Sociological Review.
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.