Ioakeim Perros
- Computational Mathematics top 0.5%
- Artificial Intelligence
- Hardware and Architecture top 10%
- Radiology, Nuclear Medicine and Imaging
- Signal Processing
- Co-authors
- Jimeng SunRichard VuducEvangelos E. PapalexakisJiajia LiElizabeth SearlesJoyce C. HoJee ChoiWalter F. Stewart
- Topics
- Tensor decomposition and applications (10 papers)Parallel Computing and Optimization Techniques (5 papers)Advanced Neuroimaging Techniques and Applications (3 papers)
- Journals
- Journal of Biomedical InformaticsCaltechAUTHORS (California Institute of Technology)PubMed
- Partner nations
- United States
In The Last Decade
Ioakeim Perros
11 papers receiving 219 citations
Peers
Comparison fields: 5 of 39
- Computational Mathematics 174
- Artificial Intelligence 90
- Hardware and Architecture 62
- Radiology, Nuclear Medicine and Imaging 49
- Signal Processing 22
Countries citing papers authored by Ioakeim Perros
This map shows the geographic impact of Ioakeim Perros'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 Ioakeim Perros with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioakeim Perros more than expected).
Fields of papers citing papers by Ioakeim Perros
This network shows the impact of papers produced by Ioakeim Perros. 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 Ioakeim Perros. The network helps show where Ioakeim Perros may publish in the future.
Co-authorship network of co-authors of Ioakeim Perros
This figure shows the co-authorship network connecting the top 25 collaborators of Ioakeim Perros. A scholar is included among the top collaborators of Ioakeim Perros 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 Ioakeim Perros. Ioakeim Perros is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 5 | |
| 3 | 22 | |
| 4 | 27 | |
| 5 | 11 | |
| 6 | 33 | |
| 7 | 18 | |
| 8 | 33 | |
| 9 | SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling | 12 |
| 10 | 37 | |
| 11 | 1 |
About Ioakeim Perros
Ioakeim Perros is a scholar working on Computational Mathematics, Hardware and Architecture and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 226 indexed citations. Recurring topics across this work include Tensor decomposition and applications (10 papers), Parallel Computing and Optimization Techniques (5 papers) and Advanced Neuroimaging Techniques and Applications (3 papers). The work is most often cited by research in Computational Mathematics (174 citations), Hardware and Architecture (62 citations) and Health Information Management (18 citations). Ioakeim Perros has collaborated with scholars based in United States. Frequent co-authors include Jimeng Sun, Richard Vuduc, Evangelos E. Papalexakis, Jiajia Li, Elizabeth Searles, Joyce C. Ho, Jee Choi, Walter F. Stewart, Michael Thompson and Fei Wang. Their work appears in journals such as Journal of Biomedical Informatics, CaltechAUTHORS (California Institute of Technology) and PubMed.
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.