Chin‐Kun Hu

7.4k total citations
282 papers, 5.8k citations indexed

About

Chin‐Kun Hu is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics and Molecular Biology. According to data from OpenAlex, Chin‐Kun Hu has authored 282 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Condensed Matter Physics, 87 papers in Statistical and Nonlinear Physics and 72 papers in Molecular Biology. Recurrent topics in Chin‐Kun Hu's work include Theoretical and Computational Physics (111 papers), Stochastic processes and statistical mechanics (65 papers) and Protein Structure and Dynamics (44 papers). Chin‐Kun Hu is often cited by papers focused on Theoretical and Computational Physics (111 papers), Stochastic processes and statistical mechanics (65 papers) and Protein Structure and Dynamics (44 papers). Chin‐Kun Hu collaborates with scholars based in Taiwan, Armenia and China. Chin‐Kun Hu's co-authors include David B. Saakian, Chai‐Yu Lin, N. Sh. Izmailian, Shang-keng Ma, Chandan Dasgupta, Mai Suan Li, Prashant M. Gade, Shura Hayryan, R. E. Amritkar and Bidhan Chandra Bag and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Chin‐Kun Hu

277 papers receiving 5.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chin‐Kun Hu Taiwan 41 2.2k 1.8k 1.5k 1.1k 1.1k 282 5.8k
Luca Peliti Italy 41 2.5k 1.1× 2.5k 1.4× 1.2k 0.8× 1.9k 1.8× 839 0.8× 115 6.5k
Igor M. Sokolov Germany 58 1.6k 0.7× 5.5k 3.1× 3.1k 2.0× 1.4k 1.3× 1.4k 1.3× 345 12.9k
Joachim Krug Germany 50 3.9k 1.8× 908 0.5× 1.2k 0.8× 1.3k 1.2× 2.2k 2.1× 196 8.9k
Michel Droz Switzerland 33 2.3k 1.0× 1.2k 0.7× 330 0.2× 752 0.7× 760 0.7× 139 4.4k
R. K. P. Zia United States 40 2.9k 1.3× 1.5k 0.8× 702 0.5× 1.2k 1.1× 1.6k 1.5× 177 5.3k
Daniel ben‐Avraham United States 39 3.5k 1.6× 5.4k 3.0× 1.7k 1.1× 1.3k 1.2× 2.6k 2.4× 132 11.0k
Charles R. Doering United States 43 1.1k 0.5× 2.7k 1.5× 799 0.5× 869 0.8× 1.4k 1.3× 161 7.0k
M. A. Virasoro Italy 30 4.0k 1.8× 2.4k 1.3× 508 0.3× 1.3k 1.1× 1.3k 1.3× 65 8.0k
Mogens H. Jensen Denmark 43 1.6k 0.8× 2.1k 1.2× 1.3k 0.9× 940 0.9× 704 0.7× 196 6.5k
José A. Carrillo United Kingdom 48 663 0.3× 1.5k 0.9× 1.1k 0.7× 300 0.3× 1.4k 1.4× 342 9.0k

Countries citing papers authored by Chin‐Kun Hu

Since Specialization
Citations

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

Fields of papers citing papers by Chin‐Kun Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chin‐Kun Hu. 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 Chin‐Kun Hu. The network helps show where Chin‐Kun Hu may publish in the future.

Co-authorship network of co-authors of Chin‐Kun Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Chin‐Kun Hu. A scholar is included among the top collaborators of Chin‐Kun Hu 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 Chin‐Kun Hu. Chin‐Kun Hu 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.
Yang, Huijie, et al.. (2023). Universality and scaling in complex networks from periods of Chinese history. Chaos An Interdisciplinary Journal of Nonlinear Science. 33(1). 11101–11101.
2.
Tomašovičová, Natália, Chih‐Wen Yang, M. Baťková, et al.. (2018). Self-assembly of hen egg white lysozyme fibrils doped with magnetic particles. Journal of Magnetism and Magnetic Materials. 471. 400–405. 6 indexed citations
3.
Saakian, David B., et al.. (2015). Exact dynamics for a mutator gene model. Chinese Journal of Physics. 53(5). 100904-1–100904-13. 8 indexed citations
4.
Hu, Chin‐Kun. (2014). Historical Review on Analytic, Monte Carlo, and Renormalization Group Approaches to Critical Phenomena of Some Lattice Models. Chinese Journal of Physics. 52(1). 1–76. 42 indexed citations
5.
Izmailian, N. Sh. & Chin‐Kun Hu. (2013). Amplitude ratios for critical systems in thec=−2universality class. Physical Review E. 87(1). 12110–12110. 4 indexed citations
6.
Ngô, Sơn Tùng, et al.. (2013). Oligomerization of Peptides LVEALYL and RGFFYT and Their Binding Affinity to Insulin. PLoS ONE. 8(6). e65358–e65358. 22 indexed citations
7.
Man, Viet Hoang, Chun‐Yu Chen, Chin‐Kun Hu, Yun‐Ru Chen, & Mai Suan Li. (2013). Discovery of Dihydrochalcone as Potential Lead for Alzheimer’s Disease: In Silico and In Vitro Study. PLoS ONE. 8(11). e79151–e79151. 33 indexed citations
8.
Izmailian, N. Sh., K. B. Oganesyan, Ming‐Chya Wu, & Chin‐Kun Hu. (2006). Finite-size corrections and scaling for the triangular lattice dimer model with periodic boundary conditions. Physical Review E. 73(1). 16128–16128. 30 indexed citations
9.
Li, Mai Suan, Chin‐Kun Hu, Dmitri K. Klimov, & D. Thirumalai. (2005). Multiple stepwise refolding of immunoglobulin domain I27 upon force quench depends on initial conditions. Proceedings of the National Academy of Sciences. 103(1). 93–98. 44 indexed citations
10.
Saakian, David B. & Chin‐Kun Hu. (2004). Eigen model as a quantum spin chain: Exact dynamics. Physical Review E. 69(2). 21913–21913. 50 indexed citations
11.
Saakian, David B. & Chin‐Kun Hu. (2004). Solvable biological evolution model with a parallel mutation-selection scheme. Physical Review E. 69(4). 46121–46121. 45 indexed citations
12.
Hu, Chin‐Kun, et al.. (2004). Stochastic dynamical model for stock-stock correlations. Physical Review E. 70(2). 26101–26101. 54 indexed citations
13.
Saakian, David B., Chin‐Kun Hu, & H. G. Khachatryan. (2004). Solvable biological evolution models with general fitness functions and multiple mutations in parallel mutation-selection scheme. Physical Review E. 70(4). 41908–41908. 26 indexed citations
14.
Hu, Chin‐Kun, et al.. (2001). New Mechanism of X-Ray Radiation from a Relativistic Charged Particle in a Dielectric Random Medium. Physical Review Letters. 86(15). 3324–3327. 4 indexed citations
15.
Lin, Chai‐Yu, Chin‐Kun Hu, & Ulrich H. E. Hansmann. (2001). Proteinlike behavior of a spin system near the transition between a ferromagnet and a spin glass. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 64(5). 52903–52903. 5 indexed citations
16.
Izmailian, N. Sh. & Chin‐Kun Hu. (2000). Exact Universal Amplitude Ratios for the Planar Ising Model and a Quantum Spin Chain. arXiv (Cornell University). 2 indexed citations
17.
Hu, Chin‐Kun. (1994). Histogram Monte Carlo Approach to Scaling Functions and Order Parameters of Phase Transition Models. 32(5). 519.
18.
Maillard, J.-M., F Y Wu, & Chin‐Kun Hu. (1992). Thermal transmissivity in discrete spin systems: formulation and applications. Journal of Physics A Mathematical and General. 25(9). 2521–2531. 4 indexed citations
19.
Hu, Chin‐Kun. (1984). Percolation Theory of Phase Transitions in Spin Models. Chinese Journal of Physics. 22(4). 1. 1 indexed citations
20.
Hu, Chin‐Kun. (1983). An Exact Renormalization Group Transformation and Properties of Positive Symmetry Matrices. Chinese Journal of Physics. 21(3). 24–30. 1 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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