John Lamperti

3.8k citations
51 papers · 2.2k · h-index 25

Impact in

    • Stochastic processes and statistical mechanics
    • Mathematical Dynamics and Fractals
  • Finance top 1%
    • Stochastic processes and financial applications
    • Financial Risk and Volatility Modeling

Papers in

    • Stochastic processes and statistical mechanics 10
    • advanced mathematical theories 4
    • Stochastic processes and financial applications 7

John Lamperti

46 papers receiving 1.7k citations

Peers

John Lamperti
Comparison fields: 5 of 93
  • Mathematical Physics 1.1k
  • Finance 638
  • Statistics and Probability 437
  • Applied Mathematics 282
  • Management Science and Operations Research 272
Replace Samuel J. Taylor with:
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Citations per field
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Samuel J. Taylor · 1×
Citations per year

Countries citing papers authored by John Lamperti

Since Specialization
Citations

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

Fields of papers citing papers by John Lamperti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside John Lamperti, 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 John Lamperti Line = papers co-authored together John Lamperti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1962318
2 1958206
3 1972176
4 1958141
5 1967125
6 1967105
7 196096
8 196480
9 197974
10 196363
11 197756
12 196254
13 197753
14 196252
15 199650
16 196246
17 196842
18 195942
19 195840
20 196137

About John Lamperti

John Lamperti is a scholar working on Mathematical Physics, Finance, Artificial Intelligence, Applied Mathematics and Statistics and Probability, having authored 51 papers that have together received 2.2k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (10 papers), Stochastic processes and financial applications (7 papers), advanced mathematical theories (4 papers), Probability and Risk Models (3 papers), Approximation Theory and Sequence Spaces (3 papers), Bayesian Methods and Mixture Models (3 papers), Mathematical functions and polynomials (2 papers) and Functional Equations Stability Results (2 papers). The work is most often cited by research in Mathematical Physics (1.1k citations), Finance (638 citations), Statistics and Probability (437 citations), Applied Mathematics (282 citations) and Management Science and Operations Research (272 citations). John Lamperti has collaborated with scholars based in United States, France and Sweden. Frequent co-authors include Patrick Suppes, Peter F. Thall, Adriano M. Garsia, Peter Ney, Paul Embrechts, Herbert L. Abrams, Matthew Leighton, Jennifer Leaning, David G. Kendall and Leopold Flatto. Their work appears in journals such as Transactions of the American Mathematical Society, Pacific Journal of Mathematics, Proceedings of the American Mathematical Society, Journal of Mathematical Analysis and Applications and Probability Theory and Related Fields.

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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