Sudip Sanyal
- Artificial Intelligence top 10%
- Atomic and Molecular Physics, and Optics
- Computer Vision and Pattern Recognition
- Health Information Management top 10%
- Information Systems
- Co-authors
- Yashwant SinghAtul KumarFumio HirataPavan ChakrabortyGaurav Singh TomarManmeet SinghAshish Kumar SrivastavaSugata Sanyal
- Topics
- Natural Language Processing Techniques (11 papers)Topic Modeling (8 papers)Spectroscopy and Quantum Chemical Studies (4 papers)
- Partner nations
- IndiaJapanSwitzerland
In The Last Decade
Sudip Sanyal
22 papers receiving 214 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 112
- Atomic and Molecular Physics, and Optics 44
- Computer Vision and Pattern Recognition 24
- Health Information Management 21
- Information Systems 21
Countries citing papers authored by Sudip Sanyal
This map shows the geographic impact of Sudip Sanyal'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 Sudip Sanyal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sudip Sanyal more than expected).
Fields of papers citing papers by Sudip Sanyal
This network shows the impact of papers produced by Sudip Sanyal. 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 Sudip Sanyal. The network helps show where Sudip Sanyal may publish in the future.
Co-authorship network of co-authors of Sudip Sanyal
This figure shows the co-authorship network connecting the top 25 collaborators of Sudip Sanyal. A scholar is included among the top collaborators of Sudip Sanyal 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 Sudip Sanyal. Sudip Sanyal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 4 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | Probabilistic Latent Semantic Analysis for Unsupervised Word Sense Disambiguation | 15 |
| 7 | 5 | |
| 8 | Novel Approach for Segmenting Fused / Merged Characters During Character Segmentation | 1 |
| 9 | 3 | |
| 10 | Dynamic Reconfiguration of Wireless Sensor Networks | 9 |
| 11 | 1 | |
| 12 | Named Entity Recognition for Indian Languages | 33 |
| 13 | 2 | |
| 14 | Optical Character Recognition for Degraded Text Documents. | 0 |
| 15 | 78 | |
| 16 | 1 | |
| 17 | 4 | |
| 18 | 4 | |
| 19 | 7 | |
| 20 | 32 |
About Sudip Sanyal
Sudip Sanyal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 26 papers that have together received 235 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (8 papers) and Spectroscopy and Quantum Chemical Studies (4 papers). The work is most often cited by research in Health Information Management (21 citations), Artificial Intelligence (112 citations) and Medical Laboratory Technology (3 citations). Sudip Sanyal has collaborated with scholars based in India, Japan and Switzerland. Frequent co-authors include Yashwant Singh, Atul Kumar, Fumio Hirata, Pavan Chakraborty, Gaurav Singh Tomar, Manmeet Singh, Ashish Kumar Srivastava, Sugata Sanyal, Pramod Kumar Sharma and Deepali Gupta. Their work appears in journals such as The Journal of Chemical Physics, Chemical Physics Letters and Expert Systems with Applications.
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.