Sourav S. Bhowmick
- Signal Processing top 1%
- Data Management and Algorithms 64
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- Complex Network Analysis Techniques 28
- Information Systems top 1%
- Web Data Mining and Analysis 40
- Artificial Intelligence top 1%
- Semantic Web and Ontologies 32
- Advanced Graph Neural Networks 24
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- Graph Theory and Algorithms 46
- Data Visualization and Analytics 21
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- Advanced Database Systems and Queries 63
Sourav S. Bhowmick
213 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 131
- Signal Processing 634
- Statistical and Nonlinear Physics 417
- Information Systems 757
- Artificial Intelligence 1.0k
- Computer Vision and Pattern Recognition 652
Countries citing papers authored by Sourav S. Bhowmick
This map shows the geographic impact of Sourav S. 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 Sourav S. Bhowmick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sourav S. Bhowmick more than expected).
Fields of papers citing papers by Sourav S. Bhowmick
This network shows the impact of papers produced by Sourav S. 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 Sourav S. Bhowmick. The network helps show where Sourav S. Bhowmick may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sourav S. Bhowmick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 1 | |
| 9 | 2021 | 9 | |
| 10 | 2020 | 2 | |
| 11 | 2020 | 46 | |
| 12 | 2019 | 6 | |
| 13 | NEURON: An Interactive Natural Language Interface for Understanding Query Execution Plans in RDBMS. | 2018 | 1 |
| 14 | Overexpression of Her2/Neu in Gastric Carcinoma: association with histological type, tumor grade and H. Pylori infection | 2016 | 2 |
| 15 | 2015 | 15 | |
| 16 | VOGUE: Towards a visual interaction-aware graph query processing framework | 2013 | 13 |
| 17 | prague: A Practical Framework for Blending Visual Subgraph Query Formulation and Query Processing | 2012 | 6 |
| 18 | 2009 | 1 | |
| 19 | 2008 | 1 | |
| 20 | Web Bags: Are they useful in a web warehouse? | 1998 | 10 |
About Sourav S. Bhowmick
Sourav S. Bhowmick is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 224 papers that have together received 2.4k indexed citations. Recurring topics across this work include Data Management and Algorithms (64 papers), Advanced Database Systems and Queries (63 papers), Graph Theory and Algorithms (46 papers), Web Data Mining and Analysis (40 papers), Semantic Web and Ontologies (32 papers), Complex Network Analysis Techniques (28 papers), Advanced Graph Neural Networks (24 papers) and Data Visualization and Analytics (21 papers). The work is most often cited by research in Signal Processing (634 citations), Statistical and Nonlinear Physics (417 citations) and Information Systems (757 citations). Sourav S. Bhowmick has collaborated with scholars based in Singapore, Hong Kong and United States. Frequent co-authors include Qiankun Zhao, Byron Choi, Aixin Sun, Wee Keong Ng, Jianliang Xu, Sanjay Madria, Hui Li, Jiangtao Cui, Shuigeng Zhou and Guozhong Li. Their work appears in journals such as Proceedings of the VLDB Endowment, Data & Knowledge Engineering, IEEE Transactions on Knowledge and Data Engineering, The VLDB Journal and ACM SIGMOD Record.
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.