Kuk-Hyun Han

3.1k total citations · 2 hit papers
19 papers, 2.1k citations indexed

About

Kuk-Hyun Han is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Kuk-Hyun Han has authored 19 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Computational Theory and Mathematics. Recurrent topics in Kuk-Hyun Han's work include Metaheuristic Optimization Algorithms Research (7 papers), Quantum Computing Algorithms and Architecture (7 papers) and Quantum Information and Cryptography (3 papers). Kuk-Hyun Han is often cited by papers focused on Metaheuristic Optimization Algorithms Research (7 papers), Quantum Computing Algorithms and Architecture (7 papers) and Quantum Information and Cryptography (3 papers). Kuk-Hyun Han collaborates with scholars based in South Korea and United States. Kuk-Hyun Han's co-authors include Jong-Hwan Kim, Ye-Hoon Kim, Yong‐Jae Kim, Jun-Su Jang, Jeff Lieberman, Cynthia Breazeal, Daniel Fuentes, Walter Dan Stiehl, Matt Berlin and Jesse Gray and has published in prestigious journals such as Nature, IEEE Transactions on Evolutionary Computation and Pattern Recognition Letters.

In The Last Decade

Kuk-Hyun Han

19 papers receiving 2.0k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Quantum-inspired evolutionary algorithm for a class of combinatorial optimization

2002 1.1k citations Kuk-Hyun Han, Jong-Hwan Kim IEEE Transactions on Evolutionary Computation profile →
Genetic quantum algorithm and its application to combinatorial optimization problem

2002 458 citations Kuk-Hyun Han, Jong-Hwan Kim profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kuk-Hyun Han South Korea	13	1.3k	380	347	322	297	19	2.1k
Ronald Parr United States	26	1.7k 1.4×	453 1.2×	280 0.8×	393 1.2×	440 1.5×	56	2.7k
Riashat Islam Canada	7	910 0.7×	395 1.0×	418 1.2×	154 0.5×	411 1.4×	9	2.1k
Una-May O’Reilly United States	26	1.6k 1.3×	558 1.5×	328 0.9×	436 1.4×	196 0.7×	147	3.0k
Matteo Hessel United Kingdom	8	1.3k 1.0×	461 1.2×	492 1.4×	197 0.6×	408 1.4×	16	2.4k
Bilal Piot United Kingdom	8	1.2k 0.9×	334 0.9×	348 1.0×	169 0.5×	415 1.4×	12	2.0k
Dan Horgan United Kingdom	5	983 0.8×	291 0.8×	305 0.9×	141 0.4×	392 1.3×	5	1.7k
Shimon Whiteson Netherlands	27	2.3k 1.8×	612 1.6×	310 0.9×	392 1.2×	462 1.6×	136	3.5k
Radu Grosu Austria	22	443 0.3×	231 0.6×	343 1.0×	302 0.9×	256 0.9×	134	1.6k
Long-Ji Lin United States	8	1.2k 0.9×	213 0.6×	225 0.6×	204 0.6×	309 1.0×	12	2.1k
Shalabh Bhatnagar India	24	1.1k 0.9×	489 1.3×	348 1.0×	518 1.6×	748 2.5×	151	2.5k

Countries citing papers authored by Kuk-Hyun Han

Since Specialization

Citations

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

Fields of papers citing papers by Kuk-Hyun Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuk-Hyun Han. 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 Kuk-Hyun Han. The network helps show where Kuk-Hyun Han may publish in the future.

Co-authorship network of co-authors of Kuk-Hyun Han

This figure shows the co-authorship network connecting the top 25 collaborators of Kuk-Hyun Han. A scholar is included among the top collaborators of Kuk-Hyun Han 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 Kuk-Hyun Han. Kuk-Hyun Han 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:

19 of 19 papers shown

Han, Kuk-Hyun, et al.. (2017). Design of Torsional Viscous Damper of Engine-driveshaft System with Time-varying Inertia. Transactions of the Korean Society for Noise and Vibration Engineering. 27(5). 593–601. 2 indexed citations

Kim, Ye-Hoon, Jong-Hwan Kim, & Kuk-Hyun Han. (2006). Quantum-inspired Multiobjective Evolutionary Algorithm for Multiobjective 0/1 Knapsack Problems. 5. 2601–2606. 68 indexed citations

Han, Kuk-Hyun & Jong-Hwan Kim. (2006). On the Analysis of the Quantum-inspired Evolutionary Algorithm with a Single Individual. 26. 2622–2629. 36 indexed citations

Stiehl, Walter Dan, Matt Berlin, Jesse Gray, et al.. (2006). The huggable. 82 indexed citations

Stiehl, Walter Dan, et al.. (2006). The huggable. 14–14. 4 indexed citations

Jang, Jun-Su, Kuk-Hyun Han, & Jong-Hwan Kim. (2005). Face detection using quantum-inspired evolutionary algorithm. 2. 2100–2106. 34 indexed citations

Jang, Jun-Su, Kuk-Hyun Han, & Jong-Hwan Kim. (2004). Evolutionary algorithm-based face verification. Pattern Recognition Letters. 25(16). 1857–1865. 15 indexed citations

Hwang, Joo-Young, et al.. (2003). A Quantum-Inspired Evolutionary Computing Algorithm for Disk Allocation Method. IEICE Transactions on Information and Systems. 86(3). 645–649. 24 indexed citations

Han, Kuk-Hyun & Jong-Hwan Kim. (2003). On setting the parameters of quantum-inspired evolutionary algorithm for practical application. 178–194 Vol.1. 46 indexed citations

10.

Han, Kuk-Hyun, et al.. (2002). Parallel quantum-inspired genetic algorithm for combinatorial optimization problem. 2. 1422–1429. 140 indexed citations

11.

Han, Kuk-Hyun, Shin Kim, Yong‐Jae Kim, Seung‐Eun Lee, & Jong-Hwan Kim. (2002). Implementation of Internet-based personal robot with Internet control architecture. 1. 217–222. 20 indexed citations

12.

Han, Kuk-Hyun, et al.. (2002). Robot Soccer System of SOTY 5 for Middle League MiroSot. 632–635. 7 indexed citations

13.

Han, Kuk-Hyun & Jong-Hwan Kim. (2002). Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Transactions on Evolutionary Computation. 6(6). 580–593. 1091 indexed citations breakdown →

14.

Han, Kuk-Hyun & Jong-Hwan Kim. (2002). Introduction of Quantum-inspired Evolutionary Algorithm. 8 indexed citations

15.

Han, Kuk-Hyun, Jin Hyoung Kim, Jong-Hwan Kim, & Shih‐Chang Hsia. (2002). Internet control of personal robot between KAIST and UC Davis. 2184–2189 vol.2. 15 indexed citations

16.

Han, Kuk-Hyun & Jong-Hwan Kim. (2002). Genetic quantum algorithm and its application to combinatorial optimization problem. 2. 1354–1360. 458 indexed citations breakdown →

17.

Kim, Jong-Hwan, Kuk-Hyun Han, Shin Kim, & Yong‐Jae Kim. (2001). Internet-Based Personal Robot System using Map-Based Localization. Nature. 207(5000). 1007–8. 3 indexed citations

18.

Han, Kuk-Hyun & Jong-Hwan Kim. (2001). Analysis of Quantum-Inspired Evolutionary Algorithm. 12 indexed citations

19.

Han, Kuk-Hyun, et al.. (2001). Internet Control Architecture for Internet-Based Personal Robot. Autonomous Robots. 10(2). 135–147. 66 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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