Young Jin Kim

613 total citations
12 papers, 214 citations indexed

About

Young Jin Kim is a scholar working on Artificial Intelligence, Aerospace Engineering and Plant Science. According to data from OpenAlex, Young Jin Kim has authored 12 papers receiving a total of 214 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Aerospace Engineering and 2 papers in Plant Science. Recurrent topics in Young Jin Kim's work include Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers) and Speech Recognition and Synthesis (2 papers). Young Jin Kim is often cited by papers focused on Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers) and Speech Recognition and Synthesis (2 papers). Young Jin Kim collaborates with scholars based in United States, South Korea and United Kingdom. Young Jin Kim's co-authors include Sun Choi, Hany Hassan, Jhoon Kim, Nikolay Bogoychev, Kenneth Heafield, Alham Fikri Aji, Roman Grundkiewicz, Marcin Junczys-Dowmunt, Jang Gyu Lee and Hyung Seok Han and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Plant Disease and Journal of Air Transport Management.

In The Last Decade

Young Jin Kim

11 papers receiving 200 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Young Jin Kim United States	7	103	46	44	28	24	12	214
Haowei Xu China	7	103 1.0×	19 0.4×	48 1.1×	33 1.2×	25 1.0×	38	261
Yong Zhong China	11	227 2.2×	48 1.0×	46 1.0×	5 0.2×	36 1.5×	36	468
Jianwu Lin China	10	192 1.9×	23 0.5×	34 0.8×	7 0.3×	11 0.5×	21	323
Chloé Friguet France	7	106 1.0×	6 0.1×	21 0.5×	37 1.3×	78 3.3×	10	383
Jianlong Wang China	10	131 1.3×	10 0.2×	34 0.8×	97 3.5×	30 1.3×	34	376
Carlos Alberto Olvera-Olvera Mexico	9	168 1.6×	7 0.2×	58 1.3×	9 0.3×	10 0.4×	33	355
Yufeng Xiao China	10	48 0.5×	12 0.3×	12 0.3×	31 1.1×	25 1.0×	49	238
S. M. Jaisakthi India	8	153 1.5×	20 0.4×	110 2.5×	5 0.2×	16 0.7×	26	396
Anderson Santos Brazil	4	73 0.7×	4 0.1×	34 0.8×	12 0.4×	31 1.3×	5	274
Weihui Zeng China	7	278 2.7×	26 0.6×	12 0.3×	7 0.3×	4 0.2×	14	353

Countries citing papers authored by Young Jin Kim

Since Specialization

Citations

This map shows the geographic impact of Young Jin 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 Young Jin Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young Jin Kim more than expected).

Fields of papers citing papers by Young Jin Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young Jin 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 Young Jin Kim. The network helps show where Young Jin Kim may publish in the future.

Co-authorship network of co-authors of Young Jin Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Young Jin Kim. A scholar is included among the top collaborators of Young Jin 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 Young Jin Kim. Young Jin Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Kim, Young Jin, et al.. (2025). Fast and Accurate Task Planning using Neuro-Symbolic Language Models and Multi-Level Goal Decomposition. 16195–16201.

2.

Pham, Hai, Young Jin Kim, Subhabrata Mukherjee, et al.. (2023). Task-Based MoE for Multitask Multilingual Machine Translation. 164–172. 1 indexed citations

3.

Jawahar, Ganesh, Subhabrata Mukherjee, Xiaodong Liu, et al.. (2023). AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. 9116–9132. 2 indexed citations

4.

Kim, Young Jin, et al.. (2022). Who Says Elephants Can’t Run: Bringing Large Scale MoE Models into Cloud Scale Production. 36–43. 7 indexed citations

5.

Choi, Sun & Young Jin Kim. (2021). Artificial neural network models for airport capacity prediction. Journal of Air Transport Management. 97. 102146–102146. 31 indexed citations

6.

Kim, Young Jin, Dimitri N. Mavris, & Richard Fujimoto. (2019). Time- and space-parallel simulation of air traffic networks. SIMULATION. 95(12). 1213–1228. 6 indexed citations

7.

Kim, Young Jin, Marcin Junczys-Dowmunt, Hany Hassan, et al.. (2019). From Research to Production and Back: Ludicrously Fast Neural Machine Translation. Edinburgh Research Explorer (University of Edinburgh). 280–288. 28 indexed citations

8.

Kim, Young Jin, et al.. (2012). Robust Parameter Design Based on Back Propagation Neural Network. Korean Management Science Review. 29(3). 81–89. 5 indexed citations

9.

Kim, Jhoon, et al.. (2003). Dependence of diffuse photosynthetically active solar irradiance on total optical depth. Journal of Geophysical Research Atmospheres. 108(D9). 21 indexed citations

10.

Lee, Jang Gyu, Hyung Seok Han, & Young Jin Kim. (2003). Guidance performance analysis of bank-to-turn (BTT) missiles. 2. 991–996. 8 indexed citations

11.

Hwang, Byung Kook & Young Jin Kim. (1990). Capsidiol production in pepper plants associated with age-related resistance to Phytophthora capsici.. Plant Pathology Journal. 6(2). 193–200. 3 indexed citations

12.

Kim, Young Jin. (1989). Expression of Age-Related Resistance in Pepper Plants Infected with Phytophthora capsici. Plant Disease. 73(9). 745–745. 102 indexed citations

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.

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