Jun Sakuma
Impact in
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data
- Cryptography and Data Security
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Safety Research top 5%
- Ethics and Social Impacts of AI
Papers in
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- Privacy-Preserving Technologies in Data 26
- Metaheuristic Optimization Algorithms Research 26
- Evolutionary Algorithms and Applications 17
- Cryptography and Data Security 14
- Adversarial Robustness in Machine Learning 12
- Domain Adaptation and Few-Shot Learning 9
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- Advanced Multi-Objective Optimization Algorithms 21
- Co-authors
- Shigenobu Kobayashi (32 shared papers)Toshihiro Kamishima (8 shared papers)Shotaro Akaho (7 shared papers)Wenjie Lu (6 shared papers)Yoshiji Yamada (25 shared papers)Michael E. Houle (1 shared paper)Ken Harada (5 shared papers)Isao Ono (18 shared papers)
In The Last Decade
Jun Sakuma
109 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 779
- Safety Research 130
- Health Informatics 20
- Computational Theory and Mathematics 230
- Signal Processing 150
Countries citing papers authored by Jun Sakuma
This map shows the geographic impact of Jun Sakuma'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 Jun Sakuma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Sakuma more than expected).
Fields of papers citing papers by Jun Sakuma
This network shows the impact of papers produced by Jun Sakuma. 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 Jun Sakuma. The network helps show where Jun Sakuma may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Sakuma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 122 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 185 | |
| 2 | 2005 | 60 | |
| 3 | 2018 | 55 | |
| 4 | 2006 | 48 | |
| 5 | 2015 | 45 | |
| 6 | 2019 | 43 | |
| 7 | 2017 | 40 | |
| 8 | 2018 | 40 | |
| 9 | Correcting Popularity Bias by Enhancing Recommendation Neutrality. | 2014 | 32 |
| 10 | 2009 | 25 | |
| 11 | 2007 | 25 | |
| 12 | 2002 | 25 | |
| 13 | 2018 | 24 | |
| 14 | Enhancement of the Neutrality in Recommendation. | 2012 | 23 |
| 15 | 2018 | 23 | |
| 16 | 2010 | 22 | |
| 17 | 2018 | 22 | |
| 18 | 2016 | 21 | |
| 19 | 2007 | 19 | |
| 20 | 2018 | 19 |
About Jun Sakuma
Jun Sakuma is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Genetics, Molecular Biology and Computer Vision and Pattern Recognition, having authored 122 papers that have together received 1.4k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (26 papers), Metaheuristic Optimization Algorithms Research (26 papers), Advanced Multi-Objective Optimization Algorithms (21 papers), Genetic Associations and Epidemiology (19 papers), Evolutionary Algorithms and Applications (17 papers), Cryptography and Data Security (14 papers), Adversarial Robustness in Machine Learning (12 papers) and Domain Adaptation and Few-Shot Learning (9 papers). The work is most often cited by research in Artificial Intelligence (779 citations), Safety Research (130 citations), Health Informatics (20 citations), Computational Theory and Mathematics (230 citations) and Signal Processing (150 citations). Jun Sakuma has collaborated with scholars based in Japan, France and Germany. Frequent co-authors include Shigenobu Kobayashi, Toshihiro Kamishima, Shotaro Akaho, Wenjie Lu, Yoshiji Yamada, Michael E. Houle, Ken Harada, Isao Ono, Hideki Asoh and Ichiro Takeuchi. Their work appears in journals such as Oncotarget, European Heart Journal, International Journal of Molecular Medicine, Biomedical Reports and Physiological Genomics.
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.