Andrew Haun
- Cognitive Neuroscience top 5%
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 2%
- Atomic and Molecular Physics, and Optics
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Giulio TononiBruce C. HansenEdward A. EssockYufeng ZhengEli PeliNaotsugu TsuchiyaYeon Jin KimMatteo Grasso
- Topics
- Visual perception and processing mechanisms (28 papers)Neural dynamics and brain function (12 papers)Color Science and Applications (7 papers)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Andrew Haun
36 papers receiving 827 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Cognitive Neuroscience 511
- Computer Vision and Pattern Recognition 246
- Media Technology 232
- Atomic and Molecular Physics, and Optics 76
- Experimental and Cognitive Psychology 71
Countries citing papers authored by Andrew Haun
This map shows the geographic impact of Andrew Haun'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 Andrew Haun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Haun more than expected).
Fields of papers citing papers by Andrew Haun
This network shows the impact of papers produced by Andrew Haun. 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 Andrew Haun. The network helps show where Andrew Haun may publish in the future.
Co-authorship network of co-authors of Andrew Haun
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Haun. A scholar is included among the top collaborators of Andrew Haun 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 Andrew Haun. Andrew Haun 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 | 1 | |
| 3 | Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical termsbreakdown → | 100 |
| 4 | 55 | |
| 5 | 22 | |
| 6 | 17 | |
| 7 | 20 | |
| 8 | 5 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 16 | |
| 12 | 37 | |
| 13 | 1 | |
| 14 | 8 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | 26 | |
| 18 | 11 | |
| 19 | 31 | |
| 20 | 4 |
About Andrew Haun
Andrew Haun is a scholar working on Cognitive Neuroscience, Media Technology and Ophthalmology, having authored 38 papers that have together received 859 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (28 papers), Neural dynamics and brain function (12 papers) and Color Science and Applications (7 papers). The work is most often cited by research in Media Technology (232 citations), Cognitive Neuroscience (511 citations) and Computer Vision and Pattern Recognition (246 citations). Andrew Haun has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Giulio Tononi, Bruce C. Hansen, Edward A. Essock, Yufeng Zheng, Eli Peli, Naotsugu Tsuchiya, Yeon Jin Kim, Matteo Grasso, Christof Koch and Larissa Albantakis. Their work appears in journals such as PLoS ONE, Trends in Cognitive Sciences and Vision 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.