Jungo Kasai
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Molecular Biology
- Management Science and Operations Research
- Co-authors
- Dragomir RadevMichihiro YasunagaNoah A. SmithAlexander R. FabbriRui ZhangIrene LiDan FriedmanChangyuan Yu
- Topics
- Topic Modeling (21 papers)Natural Language Processing Techniques (20 papers)Cardiac Arrhythmias and Treatments (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaPhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesJournal of Cardiovascular Electrophysiology
- Partner nations
- United StatesJapanIsrael
In The Last Decade
Jungo Kasai
32 papers receiving 501 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 415
- Computer Vision and Pattern Recognition 139
- Information Systems 55
- Molecular Biology 27
- Management Science and Operations Research 18
Countries citing papers authored by Jungo Kasai
This map shows the geographic impact of Jungo Kasai'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 Jungo Kasai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jungo Kasai more than expected).
Fields of papers citing papers by Jungo Kasai
This network shows the impact of papers produced by Jungo Kasai. 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 Jungo Kasai. The network helps show where Jungo Kasai may publish in the future.
Co-authorship network of co-authors of Jungo Kasai
This figure shows the co-authorship network connecting the top 25 collaborators of Jungo Kasai. A scholar is included among the top collaborators of Jungo Kasai 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 Jungo Kasai. Jungo Kasai 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 | 0 | |
| 3 | 19 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 58 | |
| 10 | 16 | |
| 11 | 12 | |
| 12 | 9 | |
| 13 | 9 | |
| 14 | 0 | |
| 15 | 30 | |
| 16 | 48 | |
| 17 | 6 | |
| 18 | Parallel Machine Translation with Disentangled Context Transformer | 12 |
| 19 | Non-autoregressive Machine Translation with Disentangled Context Transformer | 11 |
| 20 | 12 |
About Jungo Kasai
Jungo Kasai is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition, having authored 39 papers that have together received 538 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (20 papers) and Cardiac Arrhythmias and Treatments (12 papers). The work is most often cited by research in Artificial Intelligence (415 citations), Computer Vision and Pattern Recognition (139 citations) and Health Informatics (8 citations). Jungo Kasai has collaborated with scholars based in United States, Japan and Israel. Frequent co-authors include Dragomir Radev, Michihiro Yasunaga, Noah A. Smith, Alexander R. Fabbri, Rui Zhang, Irene Li, Dan Friedman, Changyuan Yu, Mari Ostendorf and Yushi Hu. Their work appears in journals such as SHILAP Revista de lepidopterología, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Journal of Cardiovascular Electrophysiology.
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.