Abhra Sarkar

25 papers receiving 335 citations

Peers

Abhra Sarkar
Comparison fields: 5 of 76
  • Developmental Biology 136
  • Pharmacy 60
  • Social Psychology 132
  • Statistics and Probability 48
  • Computational Mathematics 3
Replace Diana A. Liao with:
Diana A. Liao United States
Yayoi Teramoto United Kingdom
Yoshimasa Seki Japan
Lena Veit Germany
Sarah‐Elizabeth Byosiere United States
Piera Filippi France
Josep B. Trobalón Spain
Michelle Spierings Netherlands
Yuko Hattori Japan
Douglas K. Bemis United States
Abhra Sarkar relative to Diana A. Liao United States Diana A. Liao's profile →
Citations per field
00.5×
Diana A. Liao · 1×
Citations per year

Countries citing papers authored by Abhra Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Abhra Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015145
2 201669
3 201413
4 201713
5 201613
6 201712
7 201711
8 20219
9 20149
10 20207
11 20185
12 20235
13 20234
14 20204
15 20204
16 20232
17 20242
18 20192
19 20192
20 20241

About Abhra Sarkar

Abhra Sarkar is a scholar working on Artificial Intelligence, Statistics and Probability, Ecology, Evolution, Behavior and Systematics, Developmental Biology and Ecology, having authored 27 papers that have together received 337 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (11 papers), Statistical Methods and Bayesian Inference (9 papers), Statistical Methods and Inference (8 papers), Animal Behavior and Reproduction (4 papers), Animal Vocal Communication and Behavior (4 papers), Marine animal studies overview (3 papers), Nutritional Studies and Diet (2 papers) and Language, Metaphor, and Cognition (2 papers). The work is most often cited by research in Developmental Biology (136 citations), Pharmacy (60 citations), Social Psychology (132 citations), Statistics and Probability (48 citations) and Computational Mathematics (3 citations). Abhra Sarkar has collaborated with scholars based in United States, Australia and Switzerland. Frequent co-authors include Erich D. Jarvis, Jonathan Chabout, David B. Dunson, David B. Dunson, Raymond J. Carroll, Bani K. Mallick, Simon E. Fisher, Debdeep Pati, Bharath Chandrasekaran and Giorgio Paulon. Their work appears in journals such as Journal of the American Statistical Association, Scientific Reports, Journal of Computational and Graphical Statistics, Frontiers in Behavioral Neuroscience and Bayesian Analysis.

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