Jun Sakuma
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data 27
- Metaheuristic Optimization Algorithms Research 25
- Evolutionary Algorithms and Applications 17
- Cryptography and Data Security 15
- Adversarial Robustness in Machine Learning 11
- Domain Adaptation and Few-Shot Learning 9
- Health Informatics top 10%
- Safety Research top 5%
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- Advanced Multi-Objective Optimization Algorithms 20
- Signal Processing top 5%
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- Genetic Associations and Epidemiology 19
In The Last Decade
Jun Sakuma
108 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 125
- Artificial Intelligence 772
- Health Informatics 22
- Safety Research 128
- Computational Theory and Mathematics 225
- Signal Processing 144
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 4 | |
| 8 | 2019 | 0 | |
| 9 | 2017 | 6 | |
| 10 | 2017 | 10 | |
| 11 | Differentially Private Chi-squared Test by Unit Circle Mechanism | 2017 | 8 |
| 12 | Correcting Popularity Bias by Enhancing Recommendation Neutrality. | 2014 | 31 |
| 13 | Reliability Evaluation of ECG Signal Transmitted by IR-Based Human Body Communication | 2014 | 2 |
| 14 | Efficiency Improvement of Neutrality-Enhanced Recommendation. | 2013 | 17 |
| 15 | Privacy-preserving Online Logistic Regression Based on Homomorphic Encryption | 2013 | 0 |
| 16 | Enhancement of the Neutrality in Recommendation. | 2012 | 23 |
| 17 | Online Prediction with Privacy | 2010 | 4 |
| 18 | 2006 | 1 | |
| 19 | 3D-CT ANGIOGRAPHY WITHOUT CONVENTIONAL ANGIOGRAPHY IN ACUTE CEREBRAL ANEURYSM SURGERY | 2000 | 1 |
| 20 | 2000 | 12 |
About Jun Sakuma
Jun Sakuma is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Genetics and Management Science and Operations Research, having authored 120 papers that have together received 1.3k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (27 papers), Metaheuristic Optimization Algorithms Research (25 papers), Advanced Multi-Objective Optimization Algorithms (20 papers), Genetic Associations and Epidemiology (19 papers), Evolutionary Algorithms and Applications (17 papers), Cryptography and Data Security (15 papers), Adversarial Robustness in Machine Learning (11 papers) and Domain Adaptation and Few-Shot Learning (9 papers). The work is most often cited by research in Artificial Intelligence (772 citations), Health Informatics (22 citations), Safety Research (128 citations), Computational Theory and Mathematics (225 citations) and Signal Processing (144 citations). Jun Sakuma has collaborated with scholars based in Japan, France and Ireland. 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, Biomedical Reports, International Journal of Molecular Medicine and 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.