Harsh Dave
Impact in
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- Calcium Carbonate Crystallization and Inhibition
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- Brain Tumor Detection and Classification
Papers in
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- Digital Imaging for Blood Diseases 1
- Co-authors
- Dhairya Vyas (9 shared papers)Dr. Sheshang Degadwala (9 shared papers)Sanjay Singh (2 shared papers)Stuti Bhagat (2 shared papers)Zhenpeng Qin (2 shared papers)Xiaoqing Li (1 shared paper)Esma Khatun (1 shared paper)Miguel Angel Ruiz-Cardozo (1 shared paper)
- Journals
- Journal of Nanoscience and Nanotechnology (1 paper)Expert Review of Anti-infective Therapy (1 paper)Nanoscale (1 paper)Advanced Science (1 paper)The Journal of Physical Chemistry B (1 paper)
- Partner nations
- IndiaUnited StatesPhilippines
In The Last Decade
Harsh Dave
20 papers receiving 285 citations
Peers
Comparison fields: 5 of 115
- Biomaterials 53
- Neurology 19
- Computer Vision and Pattern Recognition 40
- Radiology, Nuclear Medicine and Imaging 34
- Structural Biology 2
Countries citing papers authored by Harsh Dave
This map shows the geographic impact of Harsh Dave'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 Dave with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harsh Dave more than expected).
Fields of papers citing papers by Harsh Dave
This network shows the impact of papers produced by Harsh Dave. 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 Dave. The network helps show where Harsh Dave may publish in the future.
Co-authors
The 25 scholars most cited alongside Harsh Dave, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 82 | |
| 2 | 2024 | 32 | |
| 3 | 2023 | 27 | |
| 4 | 2020 | 24 | |
| 5 | 2023 | 24 | |
| 6 | 2023 | 18 | |
| 7 | 2022 | 18 | |
| 8 | 2023 | 17 | |
| 9 | 2023 | 11 | |
| 10 | 2021 | 10 | |
| 11 | 2021 | 10 | |
| 12 | 2021 | 8 | |
| 13 | 2018 | 4 | |
| 14 | 2021 | 4 | |
| 15 | 2018 | 3 | |
| 16 | 2022 | 2 | |
| 17 | 2018 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2018 | 1 | |
| 20 | 2025 | 1 |
About Harsh Dave
Harsh Dave is a scholar working on Computer Vision and Pattern Recognition, Ophthalmology, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Artificial Intelligence, having authored 22 papers that have together received 299 indexed citations. Recurring topics across this work include AI in cancer detection (3 papers), Advanced Nanomaterials in Catalysis (2 papers), Retinal Imaging and Analysis (2 papers), Leaf Properties and Growth Measurement (1 paper), Cutaneous Melanoma Detection and Management (1 paper), Digital Imaging for Blood Diseases (1 paper), Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper) and Lipid Membrane Structure and Behavior (1 paper). The work is most often cited by research in Biomaterials (53 citations), Neurology (19 citations), Computer Vision and Pattern Recognition (40 citations), Radiology, Nuclear Medicine and Imaging (34 citations) and Structural Biology (2 citations). Harsh Dave has collaborated with scholars based in India, United States and Philippines. Frequent co-authors include Dhairya Vyas, Dr. Sheshang Degadwala, Sanjay Singh, Stuti Bhagat, Zhenpeng Qin, Xiaoqing Li, Esma Khatun, Miguel Angel Ruiz-Cardozo, Monica Giannotta and Thalappil Pradeep. Their work appears in journals such as Journal of Nanoscience and Nanotechnology, Expert Review of Anti-infective Therapy, Nanoscale, Advanced Science and The Journal of Physical Chemistry B.
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.