Perla Subbaiah

883 citations
35 papers · 645 · h-index 11

Impact in

Papers in

Perla Subbaiah

33 papers receiving 611 citations

Peers

Perla Subbaiah
Comparison fields: 5 of 114
  • Statistics, Probability and Uncertainty 167
  • Statistics and Probability 137
  • Management Science and Operations Research 85
  • Immunology 108
  • Hematology 55
Replace Michael Sfakianakis with:
Michael Sfakianakis Greece
Wen Wan United States
Yuhwen Soo United States
Jiacheng Yuan United States
David Tritchler Canada
Chunpeng Fan United States
Dai Feng United States
Yaohua He United States
Vanya Van Belle Belgium
Laura Azzimonti Switzerland
Perla Subbaiah relative to Michael Sfakianakis Greece Michael Sfakianakis's profile →
Citations per field
00.5×8.3×
Michael Sfakianakis · 1×
Citations per year

Countries citing papers authored by Perla Subbaiah

Since Specialization
Citations

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

Fields of papers citing papers by Perla Subbaiah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014187
2 1993153
3 198943
4 202138
5 199634
6 202223
7 201922
8 199321
9 199018
10 201115
11 198210
12 20187
13 19787
14 19746
15 19806
16 19746
17 20155
18 19845
19 19885
20 19765

About Perla Subbaiah

Perla Subbaiah is a scholar working on Statistics and Probability, Management Science and Operations Research, Epidemiology, Statistics, Probability and Uncertainty and Surgery, having authored 35 papers that have together received 645 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (9 papers), Optimal Experimental Design Methods (7 papers), Statistical Methods and Bayesian Inference (4 papers), Statistical Methods in Clinical Trials (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers), Advanced Statistical Process Monitoring (4 papers), Statistical Methods and Inference (3 papers) and Statistical Distribution Estimation and Applications (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (167 citations), Statistics and Probability (137 citations), Management Science and Operations Research (85 citations), Immunology (108 citations) and Hematology (55 citations). Perla Subbaiah has collaborated with scholars based in United States, Netherlands and South Korea. Frequent co-authors include Winson Taam, Kanakadurga Singer, Govind S. Mudholkar, Brian F. Zamarron, Lindsey A. Muir, David L. Morris, Lynn M. Geletka, Jennifer L. DelProposto, Kae Won Cho and Carey N. Lumeng. Their work appears in journals such as Journal of the American Statistical Association, Biometrical Journal, Hormone and Metabolic Research, Pediatric Critical Care Medicine and Breast Cancer Research and Treatment.

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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