Harsh Agrawal
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Mechanical Engineering
- Information Systems
- Plant Science
- Co-authors
- Jitendra KumarA.M. GokhaleYash GoyalHamish GrahamM.F. HorstemeyerDhruv BatraPeter AndersonPrabhat K. Singh
- Topics
- Sentiment Analysis and Opinion Mining (2 papers)Advanced Image and Video Retrieval Techniques (2 papers)Multimodal Machine Learning Applications (2 papers)
- Cited by
- Health Information ManagementArtificial IntelligenceComputer Graphics and Computer-Aided Design
- Journals
- Materials Science and Engineering AExperimental HematologySignal Image and Video Processing
- Partner nations
- IndiaUnited States
In The Last Decade
Harsh Agrawal
16 papers receiving 118 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 45
- Computer Vision and Pattern Recognition 22
- Mechanical Engineering 22
- Information Systems 17
- Plant Science 16
Countries citing papers authored by Harsh Agrawal
This map shows the geographic impact of Harsh Agrawal'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 Harsh Agrawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harsh Agrawal more than expected).
Fields of papers citing papers by Harsh Agrawal
This network shows the impact of papers produced by Harsh Agrawal. 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 Harsh Agrawal. The network helps show where Harsh Agrawal may publish in the future.
Co-authorship network of co-authors of Harsh Agrawal
This figure shows the co-authorship network connecting the top 25 collaborators of Harsh Agrawal. A scholar is included among the top collaborators of Harsh Agrawal 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 Harsh Agrawal. Harsh Agrawal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | 17 | |
| 10 | 12 | |
| 11 | 3 | |
| 12 | 13 | |
| 13 | Contrast and Classify: Alternate Training for Robust VQA. | 2 |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 29 | |
| 17 | 14 |
About Harsh Agrawal
Harsh Agrawal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management, having authored 17 papers that have together received 125 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Health Information Management (9 citations), Artificial Intelligence (45 citations) and Computer Graphics and Computer-Aided Design (4 citations). Harsh Agrawal has collaborated with scholars based in India and United States. Frequent co-authors include Jitendra Kumar, A.M. Gokhale, Yash Goyal, Hamish Graham, M.F. Horstemeyer, Dhruv Batra, Peter Anderson, Prabhat K. Singh, Anurag Goel and Satish Khurana. Their work appears in journals such as Materials Science and Engineering A, Experimental Hematology and Signal Image and Video Processing.
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.