Sanjukta Bhowmick
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Geophysics top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Sriram SrinivasanAnimesh MukherjeeNiloy GangulyTanmoy ChakrabortySayantan DasguptaP. K. BhattacharyaPulak SenguptaMasato Fukuoka
- Topics
- Complex Network Analysis Techniques (28 papers)Bioinformatics and Genomic Networks (14 papers)Graph Theory and Algorithms (11 papers)
- Partner nations
- United StatesIndiaJapan
In The Last Decade
Sanjukta Bhowmick
41 papers receiving 450 citations
Peers
Comparison fields: 5 of 64
- Statistical and Nonlinear Physics 200
- Artificial Intelligence 146
- Geophysics 120
- Computer Networks and Communications 100
- Computer Vision and Pattern Recognition 73
Countries citing papers authored by Sanjukta Bhowmick
This map shows the geographic impact of Sanjukta Bhowmick'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 Sanjukta Bhowmick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanjukta Bhowmick more than expected).
Fields of papers citing papers by Sanjukta Bhowmick
This network shows the impact of papers produced by Sanjukta Bhowmick. 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 Sanjukta Bhowmick. The network helps show where Sanjukta Bhowmick may publish in the future.
Co-authorship network of co-authors of Sanjukta Bhowmick
This figure shows the co-authorship network connecting the top 25 collaborators of Sanjukta Bhowmick. A scholar is included among the top collaborators of Sanjukta Bhowmick 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 Sanjukta Bhowmick. Sanjukta Bhowmick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 18 | |
| 9 | 3 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 11 | |
| 13 | 4 | |
| 14 | 7 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 28 | |
| 18 | Application of Group Testing in Identifying High Betweenness Centrality Vertices in Complex Networks | 4 |
| 19 | 3 | |
| 20 | 5 |
About Sanjukta Bhowmick
Sanjukta Bhowmick is a scholar working on Statistical and Nonlinear Physics, Software and Hardware and Architecture, having authored 49 papers that have together received 469 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (28 papers), Bioinformatics and Genomic Networks (14 papers) and Graph Theory and Algorithms (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (200 citations), Geophysics (120 citations) and Artificial Intelligence (146 citations). Sanjukta Bhowmick has collaborated with scholars based in United States, India and Japan. Frequent co-authors include Sriram Srinivasan, Animesh Mukherjee, Niloy Ganguly, Tanmoy Chakraborty, Sayantan Dasgupta, P. K. Bhattacharya, Pulak Sengupta, Masato Fukuoka, Philip Meyer and Harvey Siy. Their work appears in journals such as Scientific Reports, Journal of Petrology and IEEE Transactions on Knowledge and Data Engineering.
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.