Jae-Min Kim
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Civil and Structural Engineering top 5%
- Electrical and Electronic Engineering
- Mechanical Engineering
- Co-authors
- Eunwoo SongRyuichi YamamotoChung‐Bang YunDookie KimYoung-Sang KimIn-Hwan YangYoung‐Ha ParkMaria Q. Feng
- Topics
- Geotechnical Engineering and Underground Structures (17 papers)Speech Recognition and Synthesis (15 papers)Speech and Audio Processing (12 papers)
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Jae-Min Kim
60 papers receiving 987 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 432
- Signal Processing 419
- Civil and Structural Engineering 334
- Electrical and Electronic Engineering 136
- Mechanical Engineering 116
Countries citing papers authored by Jae-Min Kim
This map shows the geographic impact of Jae-Min Kim'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 Jae-Min Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jae-Min Kim more than expected).
Fields of papers citing papers by Jae-Min Kim
This network shows the impact of papers produced by Jae-Min Kim. 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 Jae-Min Kim. The network helps show where Jae-Min Kim may publish in the future.
Co-authorship network of co-authors of Jae-Min Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Jae-Min Kim. A scholar is included among the top collaborators of Jae-Min Kim 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 Jae-Min Kim. Jae-Min Kim 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | Parallel Wavegan: A Fast Waveform Generation Model Based on Generative Adversarial Networks with Multi-Resolution Spectrogrambreakdown → | 462 |
| 11 | 17 | |
| 12 | 4 | |
| 13 | 5 | |
| 14 | Normalisation Methods on Neural Networks for Predicting Pavement Layer Moduli | 2 |
| 15 | A Methodology for Monitoring Prestressed Force of Bridges Using OFS-embedded Stand | 2 |
| 16 | Evaluation of the Roadbed Behavior During Tilting-train Operation in Curved Track Using Numerical Analysis | 1 |
| 17 | Radial 3-D Elastodynamic Infinite Elements | 1 |
| 18 | Cuboidal Infinite Elements for Soil-Structure-Interaction Analysis in Multi-Layered Half-Space | 2 |
| 19 | Development of New Semi-solid Method and Practical Application to Bearing Bracket | 1 |
| 20 | Numerical Analysis of the Roadbed Settlement beneath Rail Joint Induced by Tilting-Train Loading | 1 |
About Jae-Min Kim
Jae-Min Kim is a scholar working on General Engineering, Civil and Structural Engineering and Signal Processing, having authored 75 papers that have together received 1.1k indexed citations. Recurring topics across this work include Geotechnical Engineering and Underground Structures (17 papers), Speech Recognition and Synthesis (15 papers) and Speech and Audio Processing (12 papers). The work is most often cited by research in Signal Processing (419 citations), Civil and Structural Engineering (334 citations) and Artificial Intelligence (432 citations). Jae-Min Kim has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Eunwoo Song, Ryuichi Yamamoto, Chung‐Bang Yun, Dookie Kim, Young-Sang Kim, Young-Sang Kim, In-Hwan Yang, Young‐Ha Park, Maria Q. Feng and Gwiy‐Sang Chung. Their work appears in journals such as Construction and Building Materials, Sensors and Chemical Engineering Science.
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.