Prabir Burman

1.7k citations
37 papers · 1.2k · h-index 16

Impact in

Papers in

Prabir Burman

33 papers receiving 1.1k citations

Peers

Prabir Burman
Comparison fields: 5 of 177
  • Statistics and Probability 226
  • Artificial Intelligence 226
  • Ecological Modeling 30
  • Global and Planetary Change 138
  • Management Science and Operations Research 70
Replace Silke Janitza with:
Silke Janitza Germany
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Prabir Burman relative to Silke Janitza Germany Silke Janitza's profile →
Citations per field
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Citations per year

Countries citing papers authored by Prabir Burman

Since Specialization
Citations

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

Fields of papers citing papers by Prabir Burman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Prabir Burman, 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 Prabir Burman Line = papers co-authored together Prabir Burman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1989465
2 1994130
3 2006110
4 201774
5 199938
6 201335
7 198932
8 198527
9 201225
10 200625
11 200822
12 198920
13 199119
14 201117
15 199016
16 202015
17 201412
18
A Validated Risk Model for 30-Day Readmission for Heart Failure.
201712
19 201610
20 199410

About Prabir Burman

Prabir Burman is a scholar working on Statistics and Probability, Artificial Intelligence, Control and Systems Engineering, Applied Mathematics and Management Science and Operations Research, having authored 37 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (9 papers), Statistical Methods and Inference (6 papers), Control Systems and Identification (5 papers), Bayesian Methods and Mixture Models (4 papers), Fault Detection and Control Systems (3 papers), Wildlife Ecology and Conservation (3 papers), Stock Market Forecasting Methods (3 papers) and Heart Failure Treatment and Management (3 papers). The work is most often cited by research in Statistics and Probability (226 citations), Artificial Intelligence (226 citations), Ecological Modeling (30 citations), Global and Planetary Change (138 citations) and Management Science and Operations Research (70 citations). Prabir Burman has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Edmond Chow, Deborah Nolan, Melissa M. Grigione, Wolfgang Polonik, Eric A. Davidson, Becky M. Pierce, Robert S. Evans, Lawrence B. Flanagan, J. William Munger and Vernon C. Bleich. Their work appears in journals such as Journal of Multivariate Analysis, Biometrika, Urban Ecosystems, The Annals of Statistics and Journal of Stroke and Cerebrovascular Diseases.

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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