B. Kahng

10.0k total citations · 1 hit paper
206 papers, 7.1k citations indexed

About

B. Kahng is a scholar working on Statistical and Nonlinear Physics, Condensed Matter Physics and Mathematical Physics. According to data from OpenAlex, B. Kahng has authored 206 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 118 papers in Statistical and Nonlinear Physics, 71 papers in Condensed Matter Physics and 43 papers in Mathematical Physics. Recurrent topics in B. Kahng's work include Complex Network Analysis Techniques (99 papers), Theoretical and Computational Physics (70 papers) and Opinion Dynamics and Social Influence (55 papers). B. Kahng is often cited by papers focused on Complex Network Analysis Techniques (99 papers), Theoretical and Computational Physics (70 papers) and Opinion Dynamics and Social Influence (55 papers). B. Kahng collaborates with scholars based in South Korea, United States and Germany. B. Kahng's co-authors include K.-I. Goh, D. Kim, Deok‐Sun Lee, Eunsoon Oh, Hawoong Jeong, Jae Sung Lee, Albert-Ĺaszló Barabási, S. Redner, Y. S. Cho and Shinbuhm Lee and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

B. Kahng

202 papers receiving 6.8k citations

Hit Papers

Universal Behavior of Load Distribution in Scale-Free Net... 2001 2026 2009 2017 2001 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
B. Kahng South Korea 43 3.6k 1.5k 1.3k 992 901 206 7.1k
D.A.J. Rand United Kingdom 59 1.8k 0.5× 3.1k 2.1× 486 0.4× 867 0.9× 2.2k 2.4× 219 12.1k
Chaoming Song United States 31 3.2k 0.9× 389 0.3× 567 0.4× 1.1k 1.1× 802 0.9× 74 9.2k
Yasuji Sawada Japan 33 1.3k 0.4× 869 0.6× 1.3k 1.0× 805 0.8× 347 0.4× 170 4.7k
Elliott W. Montroll United States 30 2.9k 0.8× 1.3k 0.9× 2.3k 1.8× 458 0.5× 1.2k 1.4× 60 12.2k
Daniel ben‐Avraham United States 39 5.4k 1.5× 293 0.2× 3.5k 2.8× 1.2k 1.2× 1.7k 1.9× 132 11.0k
S. Redner United States 57 6.9k 1.9× 213 0.1× 4.4k 3.4× 814 0.8× 1.6k 1.8× 238 13.1k
Moshe Schwartz Israel 37 598 0.2× 1.8k 1.2× 1.2k 1.0× 2.5k 2.5× 625 0.7× 299 5.6k
Jean‐Philippe Bouchaud France 55 3.6k 1.0× 271 0.2× 4.3k 3.4× 517 0.5× 1.2k 1.3× 241 15.5k
Bernardo Spagnolo Italy 68 4.5k 1.3× 1.4k 0.9× 239 0.2× 1.7k 1.7× 1.2k 1.3× 203 8.1k
Raúl Toral Spain 42 3.8k 1.0× 217 0.1× 926 0.7× 1.9k 1.9× 569 0.6× 208 6.0k

Countries citing papers authored by B. Kahng

Since Specialization
Citations

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

Fields of papers citing papers by B. Kahng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of B. Kahng

This figure shows the co-authorship network connecting the top 25 collaborators of B. Kahng. A scholar is included among the top collaborators of B. Kahng 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 B. Kahng. B. Kahng 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.
D’Souza, Raissa M., et al.. (2024). Unified framework for hybrid percolation transitions based on microscopic dynamics. Chaos Solitons & Fractals. 184. 114981–114981. 7 indexed citations
2.
Kahng, B., et al.. (2024). Hybrid synchronization with continuous varying exponent in modernized power grid. Chaos Solitons & Fractals. 186. 115315–115315. 1 indexed citations
3.
Kim, Heetae, et al.. (2024). Reinforcement learning optimizes power dispatch in decentralized power grid. Chaos Solitons & Fractals. 186. 115293–115293. 2 indexed citations
4.
Goh, K.-I., et al.. (2023). (k,q)-core decomposition of hypergraphs. Chaos Solitons & Fractals. 173. 113645–113645. 11 indexed citations
5.
Bianconi, Ginestra, Àlex Arenas, Jacob Biamonte, et al.. (2023). Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics. Journal of Physics Complexity. 4(1). 10201–10201. 48 indexed citations
6.
Kahng, B., et al.. (2022). Discontinuous percolation transitions in cluster merging processes. Journal of Physics A Mathematical and Theoretical. 55(37). 374002–374002. 2 indexed citations
7.
Yi, Sudo, et al.. (2022). Extended mean-field approach for chimera states in random complex networks. Chaos An Interdisciplinary Journal of Nonlinear Science. 32(3). 33108–33108. 1 indexed citations
8.
Kahng, B., et al.. (2017). Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study. PLoS ONE. 12(10). e0184683–e0184683. 8 indexed citations
9.
Kahng, B., et al.. (2014). Origin of Discontinuous Percolation Transition in Cluster Merging Process. arXiv (Cornell University). 1 indexed citations
10.
Lee, Jae Sung, Shinbuhm Lee, Seo Hyoung Chang, et al.. (2010). Scaling Theory for Unipolar Resistance Switching. Physical Review Letters. 105(20). 205701–205701. 69 indexed citations
11.
Goh, K.-I., Giovanni E. Salvi, B. Kahng, & D. Kim. (2006). Skeleton and Fractal Scaling in Complex Networks. Physical Review Letters. 96(1). 18701–18701. 178 indexed citations
12.
Kahng, B., et al.. (2005). Avalanche dynamics in complex networks. Bulletin of the American Physical Society. 1 indexed citations
13.
Goh, K.-I., et al.. (2005). Evolution of the protein interaction network of budding yeast: Role of the protein family compatibility constraint. Journal of the Korean Physical Society. 46(2). 551–555. 9 indexed citations
14.
Goh, K.-I., Jae Dong Noh, B. Kahng, & Doyeon Kim. (2004). Optimal transport in weighted complex networks. arXiv (Cornell University). 2 indexed citations
15.
Goh, K.-I., et al.. (2003). Hybrid network model: the protein and the protein family interaction networks. arXiv (Cornell University). 2 indexed citations
16.
Park, YoungAh, et al.. (2003). Self-organized patterns in mixtures of microtubules and motor proteins. Journal of the Korean Physical Society. 42(1). 162–166. 19 indexed citations
17.
Kim, H., Il‐Min Kim, Y. Lee, & B. Kahng. (2002). Scale-Free Network in Stock Markets. Journal of the Korean Physical Society. 40(6). 1105–1108. 47 indexed citations
18.
Kahng, B. & Hyunseok Jeong. (2001). Nanoscale Structure Formation on Sputter Eroded Surface. Journal of the Korean Physical Society. 39(3). 421–424. 2 indexed citations
19.
Park, Soo Hyung, et al.. (1999). Numerical test of the damping time of layer-by-layer growth on stochastic models. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 59(5). 6184–6187. 5 indexed citations
20.
Kim, D., et al.. (1997). Dynamics of fluctuating interfaces and related phenomena : proceedings of the fourth CTP Workshop on Statistical Physics : Seoul National University, Seoul, Korea 27-31 January 1997. WORLD SCIENTIFIC eBooks. 5 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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