John Boaz Lee
- Artificial Intelligence top 2%
- Statistical and Nonlinear Physics top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Molecular Biology
- Co-authors
- Ryan A. RossiSungchul KimNesreen K. AhmedEunyee KohXiangnan KongGiang NguyenAnup RaoRong Zhou
- Topics
- Advanced Graph Neural Networks (9 papers)Complex Network Analysis Techniques (8 papers)Graph Theory and Algorithms (2 papers)
- Cited by
- Statistical and Nonlinear PhysicsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Knowledge and Data EngineeringACM Transactions on Knowledge Discovery from DataIEEE Transactions on Emerging Topics in Computational Intelligence
- Partner nations
- United StatesPhilippinesJapan
In The Last Decade
John Boaz Lee
17 papers receiving 842 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 663
- Statistical and Nonlinear Physics 371
- Computer Vision and Pattern Recognition 174
- Information Systems 158
- Molecular Biology 121
Countries citing papers authored by John Boaz Lee
This map shows the geographic impact of John Boaz Lee'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 John Boaz Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Boaz Lee more than expected).
Fields of papers citing papers by John Boaz Lee
This network shows the impact of papers produced by John Boaz Lee. 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 John Boaz Lee. The network helps show where John Boaz Lee may publish in the future.
Co-authorship network of co-authors of John Boaz Lee
This figure shows the co-authorship network connecting the top 25 collaborators of John Boaz Lee. A scholar is included among the top collaborators of John Boaz Lee 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 John Boaz Lee. John Boaz Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 57 | |
| 3 | 40 | |
| 4 | 5 | |
| 5 | 10 | |
| 6 | 0 | |
| 7 | 154 | |
| 8 | Temporal Network Representation Learning | 1 |
| 9 | 64 | |
| 10 | 2 | |
| 11 | 39 | |
| 12 | 158 | |
| 13 | Continuous-Time Dynamic Network Embeddingsbreakdown → | 304 |
| 14 | Skip-graph: Learning graph embeddings with an encoder-decoder model | 3 |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 16 | |
| 18 | 0 | |
| 19 | 9 |
About John Boaz Lee
John Boaz Lee is a scholar working on Statistical and Nonlinear Physics, Communication and Artificial Intelligence, having authored 19 papers that have together received 868 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (9 papers), Complex Network Analysis Techniques (8 papers) and Graph Theory and Algorithms (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (371 citations), Artificial Intelligence (663 citations) and Computer Vision and Pattern Recognition (174 citations). John Boaz Lee has collaborated with scholars based in United States, Philippines and Japan. Frequent co-authors include Ryan A. Rossi, Sungchul Kim, Nesreen K. Ahmed, Eunyee Koh, Xiangnan Kong, Giang Nguyen, Anup Rao, Rong Zhou, Theodore L. Willke and Hoda Eldardiry. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Knowledge Discovery from Data and IEEE Transactions on Emerging Topics in Computational Intelligence.
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.