Mark Kelbert

46 papers receiving 274 citations

Peers

Mark Kelbert
Comparison fields: 5 of 73
  • Modeling and Simulation 64
  • Mathematical Physics 43
  • Statistics and Probability 38
  • Statistical and Nonlinear Physics 43
  • Management Science and Operations Research 38
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Fred Torcaso United States
Sasha Cyganowski Germany
Chiping Zhang China
Thierry Huillet France
Julien Salomon France
Mathieu Laurière United States
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Citations per year

Countries citing papers authored by Mark Kelbert

Since Specialization
Citations

This map shows the geographic impact of Mark Kelbert'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 Mark Kelbert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Kelbert more than expected).

Fields of papers citing papers by Mark Kelbert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark Kelbert. 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 Mark Kelbert. The network helps show where Mark Kelbert may publish in the future.

Co-authors

The 17 scholars most cited alongside Mark Kelbert, 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 Mark Kelbert Line = papers co-authored together Mark Kelbert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200524
2 200824
3 200824
4 201117
5 199816
6 201315
7 201314
8
Markov Chains : a primer in random processes and their applications
200811
9 20108
10 20178
11 20178
12 20038
13 20227
14 20177
15 20067
16 20146
17 20036
18 20006
19 20205
20 20195

About Mark Kelbert

Mark Kelbert is a scholar working on Statistics and Probability, Modeling and Simulation, Mathematical Physics, Statistical and Nonlinear Physics and Management Science and Operations Research, having authored 52 papers that have together received 286 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (8 papers), Mathematical and Theoretical Epidemiology and Ecology Models (7 papers), COVID-19 epidemiological studies (6 papers), Theoretical and Computational Physics (6 papers), Stochastic processes and financial applications (5 papers), Point processes and geometric inequalities (4 papers), Geometric Analysis and Curvature Flows (4 papers) and Evolution and Genetic Dynamics (3 papers). The work is most often cited by research in Modeling and Simulation (64 citations), Mathematical Physics (43 citations), Statistics and Probability (38 citations), Statistical and Nonlinear Physics (43 citations) and Management Science and Operations Research (38 citations). Mark Kelbert has collaborated with scholars based in United Kingdom, Russia and Brazil. Frequent co-authors include Yuri Suhov, Igor Sazonov, Mike B. Gravenor, Alexander Grigorʼyan, Yu. M. Suhov, Pavel Mozgunov, Gennady Bocharov, A.G. Wright, O. J. Boxma and Nikolai Leonenko. Their work appears in journals such as Mathematical Biosciences, Mathematical Medicine and Biology A Journal of the IMA, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Aequationes Mathematicae and The Annals of Probability.

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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