Marat Dukhan
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Co-authors
- Richard VuducXing LiuJee ChoiBoRui WuYanghan WangMatt UyttendaeleNiraj K. JhaFei Sun
- Topics
- Parallel Computing and Optimization Techniques (3 papers)Advanced Neural Network Applications (2 papers)Domain Adaptation and Few-Shot Learning (2 papers)
- Journals
- The International Journal of High Performance Computing ApplicationsIEEE International Conference on High Performance Computing, Data, and Analytics
- Partner nations
- United StatesIsraelChina
In The Last Decade
Marat Dukhan
8 papers receiving 255 citations
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 147
- Artificial Intelligence 125
- Hardware and Architecture 82
- Computer Networks and Communications 67
- Electrical and Electronic Engineering 49
Countries citing papers authored by Marat Dukhan
This map shows the geographic impact of Marat Dukhan'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 Marat Dukhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marat Dukhan more than expected).
Fields of papers citing papers by Marat Dukhan
This network shows the impact of papers produced by Marat Dukhan. 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 Marat Dukhan. The network helps show where Marat Dukhan may publish in the future.
Co-authorship network of co-authors of Marat Dukhan
This figure shows the co-authorship network connecting the top 25 collaborators of Marat Dukhan. A scholar is included among the top collaborators of Marat Dukhan 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 Marat Dukhan. Marat Dukhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 156 | |
| 3 | 19 | |
| 4 | 19 | |
| 5 | 1 | |
| 6 | 50 | |
| 7 | 6 | |
| 8 | 7 |
About Marat Dukhan
Marat Dukhan is a scholar working on Hardware and Architecture, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 266 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (3 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Hardware and Architecture (82 citations), Computer Vision and Pattern Recognition (147 citations) and Artificial Intelligence (125 citations). Marat Dukhan has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Richard Vuduc, Xing Liu, Jee Choi, BoRui Wu, Yanghan Wang, Matt Uyttendaele, Niraj K. Jha, Fei Sun, Yangqing Jia and Hongxu Yin. Their work appears in journals such as The International Journal of High Performance Computing Applications and IEEE International Conference on High Performance Computing, Data, and Analytics.
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.