Jim Pitman

12.3k total citations · 2 hit papers
138 papers, 5.7k citations indexed

About

Jim Pitman is a scholar working on Mathematical Physics, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Jim Pitman has authored 138 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Mathematical Physics, 58 papers in Artificial Intelligence and 37 papers in Statistics and Probability. Recurrent topics in Jim Pitman's work include Stochastic processes and statistical mechanics (76 papers), Bayesian Methods and Mixture Models (55 papers) and Stochastic processes and financial applications (24 papers). Jim Pitman is often cited by papers focused on Stochastic processes and statistical mechanics (76 papers), Bayesian Methods and Mixture Models (55 papers) and Stochastic processes and financial applications (24 papers). Jim Pitman collaborates with scholars based in United States, France and United Kingdom. Jim Pitman's co-authors include Marc Yor, Jean Picard, Alexander Gnedin, David Aldous, Mihael Perman, Priscilla E. Greenwood, L. C. G. Rogers, Steven N. Evans, Philippe Biane and Richard P. Stanley and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Lecture notes in mathematics and Journal of Mathematical Analysis and Applications.

In The Last Decade

Jim Pitman

133 papers receiving 5.3k citations

Hit Papers

The two-parameter Poisson-Dirichlet distribution derived ... 1997 2026 2006 2016 1997 2006 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jim Pitman United States 39 2.8k 2.5k 1.8k 1.1k 525 138 5.7k
Amir Dembo United States 36 2.5k 0.9× 1.8k 0.7× 2.1k 1.2× 1.4k 1.3× 708 1.3× 136 8.4k
Ofer Zeitouni Israel 30 3.3k 1.2× 1.5k 0.6× 2.9k 1.6× 1.5k 1.4× 874 1.7× 179 8.5k
E. Seneta Australia 39 2.7k 1.0× 1.3k 0.5× 2.3k 1.3× 2.1k 1.9× 427 0.8× 291 9.3k
Michel Talagrand France 39 2.8k 1.0× 1.2k 0.5× 2.3k 1.3× 932 0.8× 884 1.7× 237 7.4k
Geoffrey Grimmett United Kingdom 29 2.4k 0.9× 733 0.3× 1.7k 0.9× 361 0.3× 1.4k 2.6× 123 5.7k
Yuval Peres United States 42 4.6k 1.7× 1.3k 0.5× 2.8k 1.5× 332 0.3× 1.4k 2.7× 289 8.1k
Svante Janson Sweden 41 3.7k 1.3× 1.3k 0.5× 1.8k 1.0× 499 0.4× 561 1.1× 302 8.7k
PE United States 15 839 0.3× 941 0.4× 1.1k 0.6× 745 0.7× 277 0.5× 25 5.4k
Marc Yor France 40 3.7k 1.3× 1.2k 0.5× 1.8k 1.0× 7.1k 6.3× 470 0.9× 174 10.7k
Kai Lai Chung United States 25 2.3k 0.8× 904 0.4× 1.4k 0.8× 1.3k 1.2× 369 0.7× 92 6.4k

Countries citing papers authored by Jim Pitman

Since Specialization
Citations

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

Fields of papers citing papers by Jim Pitman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jim Pitman

This figure shows the co-authorship network connecting the top 25 collaborators of Jim Pitman. A scholar is included among the top collaborators of Jim Pitman 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 Jim Pitman. Jim Pitman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Maher, Toby M., John Hood, Jim Pitman, et al.. (2025). Taladegib for the treatment of idiopathic pulmonary fibrosis (ENV-IPF-101): a multicentre, randomised, double-blind, placebo-controlled, phase 2a trial. The Lancet Respiratory Medicine. 13(11). 1001–1010.
2.
Pitman, Jim & Matthias Winkel. (2018). Squared Bessel processes of positive and negative dimension embedded in\n Brownian local times. Oxford University Research Archive (ORA) (University of Oxford). 9 indexed citations
3.
Winkel, Matthias, Jim Pitman, Grégory Miermont, & Bénédicte Haas. (2009). Continuum tree asymptotics of discrete fragmentations and applications to phylogenetic models. Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine). 9 indexed citations
4.
Pitman, Jim. (2002). Forest Volume Decompositions and Abel–Cayley–Hurwitz Multinomial Expansions. Journal of Combinatorial Theory Series A. 98(1). 175–191. 14 indexed citations
5.
Aldous, David & Jim Pitman. (2002). The asymptotic distribution of the diameter of a random mapping. Comptes Rendus Mathématique. 334(11). 1021–1024. 4 indexed citations
6.
Ismail, Mourad E. H. & Jim Pitman. (2000). Algebraic Evaluations of Some Euler Integrals, Duplication Formulae for Appell's Hypergeometric Function F1, and Brownian Variations. Canadian Journal of Mathematics. 52(5). 961–981. 15 indexed citations
7.
Pitman, Jim. (1999). Coalescents With Multiple Collisions. The Annals of Probability. 27(4). 300 indexed citations
8.
Pitman, Jim. (1999). Coalescents With Multiple Collisions. The Annals of Probability. 27(4). 1870–1902. 138 indexed citations
9.
Pitman, Jim & Marc Yor. (1999). Path decompositions of a Brownian bridge related to the ratio of its maximum and amplitude. Studia Scientiarum Mathematicarum Hungarica. 35(520). 5 indexed citations
10.
Pitman, Jim. (1999). Coalescent Random Forests. Journal of Combinatorial Theory Series A. 85(2). 165–193. 48 indexed citations
11.
Fitzsimmons, P. J. & Jim Pitman. (1999). Kac’s moment formula and the Feynman–Kac formula for additive functionals of a Markov process. Stochastic Processes and their Applications. 79(1). 117–134. 43 indexed citations
12.
Evans, Steven N. & Jim Pitman. (1998). Stationary Markov processes related to stable Ornstein–Uhlenbeck processes and the additive coalescent. Stochastic Processes and their Applications. 77(2). 175–185. 4 indexed citations
13.
Pitman, Jim. (1997). Some Probabilistic Aspects of Set Partitions. American Mathematical Monthly. 104(3). 201–209. 40 indexed citations
14.
Pitman, Jim. (1997). Probabilistic Bounds on the Coefficients of Polynomials with Only Real Zeros. Journal of Combinatorial Theory Series A. 77(2). 279–303. 59 indexed citations
15.
Diaconis, Persi, James Allen Fill, & Jim Pitman. (1992). Analysis of Top To Random Shuffles. Combinatorics Probability Computing. 1(2). 135–155. 37 indexed citations
16.
Freedman, David A. & Jim Pitman. (1990). A measure which is singular and uniformly locally uniform. Proceedings of the American Mathematical Society. 108(2). 371–381.
17.
Dubins, Lester E. & Jim Pitman. (1980). A divergent, two-parameter, bounded martingale. Proceedings of the American Mathematical Society. 78(3). 414–416. 4 indexed citations
18.
Dubins, Lester E. & Jim Pitman. (1979). A Pointwise Ergodic Theorem for the Group of Rational Rotations. Transactions of the American Mathematical Society. 251. 299–299. 2 indexed citations
19.
Dubins, Lester E. & Jim Pitman. (1979). A pointwise ergodic theorem for the group of rational rotations. Transactions of the American Mathematical Society. 251(0). 299–308. 8 indexed citations
20.
Pitman, Jim & Terence P. Speed. (1973). A note on random times. Stochastic Processes and their Applications. 1(4). 369–374. 25 indexed citations

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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