Subha Chakraborti

1.1k citations
20 papers · 800 indexed · h-index 12

Subha Chakraborti

20 papers receiving 789 citations

Peers

Subha Chakraborti
Comparison fields: 5 of 84
  • Epidemiology 414
  • Statistics, Probability and Uncertainty 293
  • Infectious Diseases 257
  • Small Animals 217
  • Statistics and Probability 174
Replace Jennifer R. Cook with:
Jennifer R. Cook South Africa
Michele Scagliarini Italy
James D. Williams United States
Mostafa Essam Eissa Egypt
Michael Bourque United States
Chenyu Han China
Richard C. Barton United Kingdom
Amit Kaushik United States
Clifford J. Maloney United States
Divya Gopinath Malaysia
Subha Chakraborti relative to Jennifer R. Cook South Africa Jennifer R. Cook's profile →
Citations per field
00.5×20×40×60×
Jennifer R. Cook · 1×
Citations per year

Countries citing papers authored by Subha Chakraborti

Since Specialization
Citations

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

Fields of papers citing papers by Subha Chakraborti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subha Chakraborti

This figure shows the co-authorship network connecting the top 25 collaborators of Subha Chakraborti. A scholar is included among the top collaborators of Subha Chakraborti 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 Subha Chakraborti. Subha Chakraborti 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
#WorkIndexed citations
1 5
2 4
3 7
4 5
5 4
6 5
7 14
8 13
9 42
10 18
11 20
12 21
13 5
14 28
15 52
16
Parameter estimation and design considerations in prospective applications of the X chart
1
17 50
18 464
19 19
20 23

About Subha Chakraborti

Subha Chakraborti is a scholar working on Statistics, Probability and Uncertainty, Medical Laboratory Technology and Statistics and Probability, having authored 20 papers that have together received 800 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (17 papers), Scientific Measurement and Uncertainty Evaluation (14 papers) and Advanced Statistical Methods and Models (9 papers). The work is most often cited by research in Microbiology (31 citations), Statistics, Probability and Uncertainty (293 citations) and Small Animals (217 citations). Subha Chakraborti has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include David J. Weber, Kenneth N. Olivier, Yansheng Zhang, Lloyd J. Edwards, Allison Handler, Michael S. Schechter, Ji‐Hyun Lee, Richard J. Wallace, Rebecca W. Wilson and Michael R. Knowles. Their work appears in journals such as Journal of the American Statistical Association, American Journal of Respiratory and Critical Care Medicine and International Journal of Production Research.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026