Kevin de Haan
- Biophysics top 0.2%
- Artificial Intelligence top 5%
- Biomedical Engineering top 10%
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 1%
- Co-authors
- Aydogan ÖzcanYair RivensonYichen WuYibo ZhangZhensong WeiTairan LiuWilliam D. WallaceJonathan E. Zuckerman
- Topics
- Cell Image Analysis Techniques (20 papers)Image Processing Techniques and Applications (13 papers)Digital Holography and Microscopy (11 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaCancer Research
- Partner nations
- United StatesRussiaCanada
In The Last Decade
Kevin de Haan
36 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Biophysics 705
- Artificial Intelligence 465
- Biomedical Engineering 422
- Computer Vision and Pattern Recognition 404
- Media Technology 398
Countries citing papers authored by Kevin de Haan
This map shows the geographic impact of Kevin de Haan'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 Kevin de Haan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin de Haan more than expected).
Fields of papers citing papers by Kevin de Haan
This network shows the impact of papers produced by Kevin de Haan. 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 Kevin de Haan. The network helps show where Kevin de Haan may publish in the future.
Co-authorship network of co-authors of Kevin de Haan
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin de Haan. A scholar is included among the top collaborators of Kevin de Haan 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 Kevin de Haan. Kevin de Haan 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 | 18 | |
| 3 | 16 | |
| 4 | 39 | |
| 5 | 24 | |
| 6 | 64 | |
| 7 | 25 | |
| 8 | Deep learning-based transformation of H&E stained tissues into special stainsbreakdown → | 185 |
| 9 | 5 | |
| 10 | 64 | |
| 11 | 101 | |
| 12 | 45 | |
| 13 | 2 | |
| 14 | PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learningbreakdown → | 255 |
| 15 | 98 | |
| 16 | 91 | |
| 17 | 25 | |
| 18 | Virtual histological staining of unlabelled tissue-autofluorescence images via deep learningbreakdown → | 406 |
| 19 | 35 | |
| 20 | 2 |
About Kevin de Haan
Kevin de Haan is a scholar working on Biophysics, Media Technology and Acoustics and Ultrasonics, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (20 papers), Image Processing Techniques and Applications (13 papers) and Digital Holography and Microscopy (11 papers). The work is most often cited by research in Biophysics (705 citations), Media Technology (398 citations) and Structural Biology (55 citations). Kevin de Haan has collaborated with scholars based in United States, Russia and Canada. Frequent co-authors include Aydogan Özcan, Yair Rivenson, Yichen Wu, Yibo Zhang, Zhensong Wei, Tairan Liu, William D. Wallace, Jonathan E. Zuckerman, Anthony Sisk and Hongda Wang. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Cancer Research.
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.