Jungeun Kim

6.3k total citations · 2 hit papers
157 papers, 4.9k citations indexed

About

Jungeun Kim is a scholar working on Artificial Intelligence, Materials Chemistry and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Jungeun Kim has authored 157 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 32 papers in Materials Chemistry and 29 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Jungeun Kim's work include Metal-Organic Frameworks: Synthesis and Applications (15 papers), Complex Network Analysis Techniques (14 papers) and Magnetism in coordination complexes (12 papers). Jungeun Kim is often cited by papers focused on Metal-Organic Frameworks: Synthesis and Applications (15 papers), Complex Network Analysis Techniques (14 papers) and Magnetism in coordination complexes (12 papers). Jungeun Kim collaborates with scholars based in South Korea, Japan and Lebanon. Jungeun Kim's co-authors include Masaki Takata, Kenichi Kato, Takuzo Aida, Susumu Kitagawa, Yutaka Moritomo, Daigo Miyajima, Fumito Araoka, Hideo Takezoe, Junaid Rashid and Sono Sasaki and has published in prestigious journals such as Science, Journal of the American Chemical Society and Angewandte Chemie International Edition.

In The Last Decade

Jungeun Kim

139 papers receiving 4.8k citations

Hit Papers

π-Conjugated Nickel Bis(dithiolene) Complex Nanosheet 2010 2026 2015 2020 2013 2010 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jungeun Kim South Korea 34 2.2k 1.3k 1.3k 1.2k 654 157 4.9k
Partha Pratim Ray India 38 2.2k 1.0× 2.3k 1.7× 1.6k 1.3× 1.2k 1.1× 651 1.0× 261 6.7k
Dongwoo Kim South Korea 30 1.7k 0.8× 1.3k 1.0× 738 0.6× 364 0.3× 1.7k 2.6× 137 4.7k
Xiao‐Yuan Wu China 37 2.8k 1.3× 2.9k 2.2× 1.3k 1.0× 785 0.7× 1.0k 1.6× 193 5.7k
Jacqueline M. Cole United Kingdom 44 5.0k 2.3× 743 0.6× 1.3k 1.0× 1.5k 1.3× 1.1k 1.7× 216 8.4k
Ejaz Ahmed Pakistan 48 4.7k 2.1× 615 0.5× 1.1k 0.8× 2.3k 2.0× 1.0k 1.6× 203 8.4k
Y. Nemoto Japan 33 2.4k 1.1× 346 0.3× 859 0.7× 2.0k 1.7× 697 1.1× 162 5.3k
Guozhen Zhang China 40 3.1k 1.4× 446 0.3× 363 0.3× 1.8k 1.5× 464 0.7× 264 6.0k
Jun Lu China 55 7.0k 3.2× 647 0.5× 1.2k 1.0× 3.6k 3.1× 634 1.0× 283 10.5k
Cheng Lü China 43 4.6k 2.1× 1.4k 1.1× 759 0.6× 1.2k 1.0× 283 0.4× 318 6.9k
Henry C. Foley United States 35 2.7k 1.2× 964 0.7× 1.0k 0.8× 938 0.8× 352 0.5× 126 4.7k

Countries citing papers authored by Jungeun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jungeun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jungeun Kim

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

All Works

20 of 20 papers shown
1.
Kim, Jungeun, et al.. (2024). Prediction of Remaining Useful Life of Battery Using Partial Discharge Data. Electronics. 13(17). 3475–3475.
2.
Ahmad, Sultan, et al.. (2024). Deep Learning Based Vehicle Detection and Counting System for Intelligent Transportation. Computer Systems Science and Engineering. 48(1). 115–130. 4 indexed citations
3.
4.
Gulistan, Muhammad, et al.. (2023). A Novel Method for Determining Tourism Carrying Capacity in a Decision-Making Context Using <i>q</i>−Rung Orthopair Fuzzy Hypersoft Environment. Computer Modeling in Engineering & Sciences. 138(2). 1951–1979. 1 indexed citations
5.
Singh, Prabhishek, Manoj Diwakar, Vijendra Singh, Seifedine Kadry, & Jungeun Kim. (2023). A new local structural similarity fusion-based thresholding method for homomorphic ultrasound image despeckling in NSCT domain. Journal of King Saud University - Computer and Information Sciences. 35(7). 101607–101607. 11 indexed citations
6.
Das, Sujit Kumar, Pinki Roy, Prabhishek Singh, et al.. (2023). Diabetic Foot Ulcer Identification: A Review. Diagnostics. 13(12). 1998–1998. 20 indexed citations
7.
Diwakar, Manoj, et al.. (2023). Multi-Document News Web Page Summarization Using Content Extraction and Lexical Chain Based Key Phrase Extraction. Mathematics. 11(8). 1762–1762. 3 indexed citations
8.
Diwakar, Manoj, et al.. (2023). Machine Translation Systems Based on Classical-Statistical-Deep-Learning Approaches. Electronics. 12(7). 1716–1716. 19 indexed citations
10.
Rashid, Junaid, Jungeun Kim, Amir Hussain, & Usman Naseem. (2023). WETM: A word embedding-based topic model with modified collapsed Gibbs sampling for short text. Pattern Recognition Letters. 172. 158–164. 3 indexed citations
11.
Raza, Mudassar, et al.. (2023). White blood cell image analysis for infection detection based on virtual hexagonal trellis (VHT) by using deep learning. Scientific Reports. 13(1). 17827–17827. 5 indexed citations
13.
Ali, Husan, et al.. (2022). Dynamic Modeling of a Nonlinear Two-Wheeled Robot Using Data-Driven Approach. Processes. 10(3). 524–524. 8 indexed citations
14.
Lim, Sungsu, et al.. (2022). OCSM : Finding overlapping cohesive subgraphs with minimum degree. Information Sciences. 607. 585–602. 3 indexed citations
15.
Nisar, Muhammad Wasif, et al.. (2021). A Novel Fingerprinting Technique for Data Storing and Sharing through Clouds. Sensors. 21(22). 7647–7647. 5 indexed citations
16.
Nazir, Tahira, Marriam Nawaz, Junaid Rashid, et al.. (2021). Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model. Sensors. 21(16). 5283–5283. 87 indexed citations
17.
Choi, Jong-Soo, Dong-Su Kim, Yu-Lim Choi, et al.. (2019). Efficacy of Starch and PVA (polyvinyl alcohol) for the Suppression of Soil Dust Emissions from Large-scale Construction Sites in Urban Areas. Journal of Soil and Groundwater Environment. 24(6). 9–15. 2 indexed citations
18.
Park, Hyunsun, et al.. (2014). A Study of Changes on the Impact of Parental Bonding on Adolescents' Academic Stress: A Moderating Effect of Parental Monitoring. Korean Journal of Youth Studies. 21(9). 123–145. 1 indexed citations
19.
Moritomo, Yutaka, et al.. (2011). Cubic-Rhombohedral Structural Phase Transition in Na1.32Mn[Fe(CN)6]0.83·3.6H2O. Journal of the Physical Society of Japan. 80(7). 74608–74608. 38 indexed citations
20.
Kato, Kenichi, Raita Hirose, Michitaka Takemoto, et al.. (2010). The RIKEN Materials Science Beamline at SPring-8: Towards Visualization of Electrostatic Interaction. AIP conference proceedings. 875–878. 77 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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