Dongryeol Lee
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Automotive Engineering
- Pollution
- Co-authors
- Kihwan KimIrfan EssaAlexander GrayParikshit RamDaehee ChoiJin-Young JungAndrew MoorePing Wang
- Topics
- Algorithms and Data Compression (8 papers)Topic Modeling (3 papers)Electromagnetic Scattering and Analysis (3 papers)
- Journals
- Journal of Computational PhysicsReview of Financial StudiesInternational Journal of Hydrogen Energy
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
Dongryeol Lee
20 papers receiving 300 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 160
- Artificial Intelligence 144
- Signal Processing 49
- Automotive Engineering 44
- Pollution 27
Countries citing papers authored by Dongryeol Lee
This map shows the geographic impact of Dongryeol 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 Dongryeol Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongryeol Lee more than expected).
Fields of papers citing papers by Dongryeol Lee
This network shows the impact of papers produced by Dongryeol 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 Dongryeol Lee. The network helps show where Dongryeol Lee may publish in the future.
Co-authorship network of co-authors of Dongryeol Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Dongryeol Lee. A scholar is included among the top collaborators of Dongryeol 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 Dongryeol Lee. Dongryeol 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 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 31 | |
| 8 | 8 | |
| 9 | 6 | |
| 10 | 23 | |
| 11 | 1 | |
| 12 | 12 | |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 21 | |
| 16 | 117 | |
| 17 | Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions | 12 |
| 18 | Linear-time Algorithms for Pairwise Statistical Problems | 23 |
| 19 | Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method | 14 |
| 20 | Fast Mean Shift with Accurate and Stable Convergence | 25 |
About Dongryeol Lee
Dongryeol Lee is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 318 indexed citations. Recurring topics across this work include Algorithms and Data Compression (8 papers), Topic Modeling (3 papers) and Electromagnetic Scattering and Analysis (3 papers). The work is most often cited by research in Computational Mathematics (6 citations), Computer Vision and Pattern Recognition (160 citations) and Signal Processing (49 citations). Dongryeol Lee has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Kihwan Kim, Irfan Essa, Alexander Gray, Parikshit Ram, Daehee Choi, Jin-Young Jung, Andrew Moore, Ping Wang, James M. Rehg and Richard Vuduc. Their work appears in journals such as Journal of Computational Physics, Review of Financial Studies and International Journal of Hydrogen Energy.
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.