Shobeir Fakhraei
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Co-authors
- Lise GetoorDhanya SridharJames R. FouldsLouiqa RaschidBert HuangHamid Soltanian‐ZadehFarshad FotouhiMadhusudana Shashanka
- Topics
- Biomedical Text Mining and Ontologies (4 papers)Computational Drug Discovery Methods (4 papers)Data Mining Algorithms and Applications (3 papers)
- Cited by
- Computational Theory and MathematicsComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- BioinformaticsExpert Systems with ApplicationsIEEE/ACM Transactions on Computational Biology and Bioinformatics
- Partner nations
- United StatesIran
In The Last Decade
Shobeir Fakhraei
15 papers receiving 435 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 172
- Computational Theory and Mathematics 146
- Molecular Biology 145
- Computer Vision and Pattern Recognition 112
- Information Systems 86
Countries citing papers authored by Shobeir Fakhraei
This map shows the geographic impact of Shobeir Fakhraei'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 Shobeir Fakhraei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shobeir Fakhraei more than expected).
Fields of papers citing papers by Shobeir Fakhraei
This network shows the impact of papers produced by Shobeir Fakhraei. 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 Shobeir Fakhraei. The network helps show where Shobeir Fakhraei may publish in the future.
Co-authorship network of co-authors of Shobeir Fakhraei
This figure shows the co-authorship network connecting the top 25 collaborators of Shobeir Fakhraei. A scholar is included among the top collaborators of Shobeir Fakhraei 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 Shobeir Fakhraei. Shobeir Fakhraei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 95 | |
| 5 | 64 | |
| 6 | Data Analytics for Pharmaceutical Discoveries | 1 |
| 7 | 54 | |
| 8 | 33 | |
| 9 | 76 | |
| 10 | 12 | |
| 11 | Predictable Dual-View Hashing | 82 |
| 12 | 3 | |
| 13 | 6 | |
| 14 | 7 | |
| 15 | 4 | |
| 16 | 3 |
About Shobeir Fakhraei
Shobeir Fakhraei is a scholar working on Computational Theory and Mathematics, Information Systems and Artificial Intelligence, having authored 16 papers that have together received 444 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (4 papers), Computational Drug Discovery Methods (4 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Computational Theory and Mathematics (146 citations), Computer Vision and Pattern Recognition (112 citations) and Artificial Intelligence (172 citations). Shobeir Fakhraei has collaborated with scholars based in United States and Iran. Frequent co-authors include Lise Getoor, Dhanya Sridhar, James R. Foulds, Louiqa Raschid, Bert Huang, Hamid Soltanian‐Zadeh, Farshad Fotouhi, Madhusudana Shashanka, Jonghyun Choi and Mohammad Rastegari. Their work appears in journals such as Bioinformatics, Expert Systems with Applications and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
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.