Sanyam Shukla
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Radiology, Nuclear Medicine and Imaging top 10%
- Information Systems top 5%
- Co-authors
- Sanjay Kumar YadavBhagat Singh RaghuwanshiRajesh WadhvaniManasi GyanchandaniRam Narayan YadavJivitesh SharmaSaurabh ShrivastavaNilay Khare
- Topics
- Machine Learning and ELM (29 papers)Face and Expression Recognition (21 papers)Imbalanced Data Classification Techniques (19 papers)
- Cited by
- Artificial IntelligenceHealth Information ManagementComputer Vision and Pattern Recognition
- Partner nations
- India
In The Last Decade
Sanyam Shukla
49 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Artificial Intelligence 836
- Computer Vision and Pattern Recognition 301
- Electrical and Electronic Engineering 218
- Radiology, Nuclear Medicine and Imaging 148
- Information Systems 124
Countries citing papers authored by Sanyam Shukla
This map shows the geographic impact of Sanyam Shukla'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 Sanyam Shukla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanyam Shukla more than expected).
Fields of papers citing papers by Sanyam Shukla
This network shows the impact of papers produced by Sanyam Shukla. 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 Sanyam Shukla. The network helps show where Sanyam Shukla may publish in the future.
Co-authorship network of co-authors of Sanyam Shukla
This figure shows the co-authorship network connecting the top 25 collaborators of Sanyam Shukla. A scholar is included among the top collaborators of Sanyam Shukla 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 Sanyam Shukla. Sanyam Shukla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 11 | |
| 8 | 5 | |
| 9 | 7 | |
| 10 | 10 | |
| 11 | 40 | |
| 12 | 31 | |
| 13 | 1 | |
| 14 | 13 | |
| 15 | 69 | |
| 16 | 26 | |
| 17 | 0 | |
| 18 | 28 | |
| 19 | 8 | |
| 20 | 2 |
About Sanyam Shukla
Sanyam Shukla is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics, having authored 55 papers that have together received 1.5k indexed citations. Recurring topics across this work include Machine Learning and ELM (29 papers), Face and Expression Recognition (21 papers) and Imbalanced Data Classification Techniques (19 papers). The work is most often cited by research in Artificial Intelligence (836 citations), Health Information Management (91 citations) and Computer Vision and Pattern Recognition (301 citations). Sanyam Shukla has collaborated with scholars based in India. Frequent co-authors include Sanjay Kumar Yadav, Bhagat Singh Raghuwanshi, Rajesh Wadhvani, Manasi Gyanchandani, Ram Narayan Yadav, Jivitesh Sharma, Saurabh Shrivastava, Nilay Khare, Sweta Jain and Kusum Kumari Bharti. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.
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.