Tae-Wook Ko

15 papers receiving 540 citations

Peers

Tae-Wook Ko
Comparison fields: 5 of 61
  • Statistical and Nonlinear Physics 168
  • Computer Networks and Communications 278
  • Cognitive Neuroscience 207
  • Materials Chemistry 169
  • Electrical and Electronic Engineering 137
Replace Maosheng Wang with:
Maosheng Wang China
Gang Dou China
Konrad Schönleber Germany
C. A. S. Batista Brazil
Д. В. Гусейнов Russia
Jinming Luo China
P. A. Subha India
Seon Hee Park South Korea
Junlong Li China
Tae-Wook Ko relative to Maosheng Wang China Maosheng Wang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Tae-Wook Ko

Since Specialization
Citations

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

Fields of papers citing papers by Tae-Wook Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tae-Wook Ko. 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 Tae-Wook Ko. The network helps show where Tae-Wook Ko may publish in the future.

Co-authors

The 23 scholars most cited alongside Tae-Wook Ko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tae-Wook Ko Line = papers co-authored together Tae-Wook Ko links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2019186
2 200762
3 200951
4 200950
5 200849
6 200244
7 200443
8 201722
9 200418
10 200811
11 20125
12 20005
13 20195
14 20214
15 20203
16 20021

About Tae-Wook Ko

Tae-Wook Ko is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Cognitive Neuroscience, Atomic and Molecular Physics, and Optics and Materials Chemistry, having authored 16 papers that have together received 559 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (12 papers), Neural dynamics and brain function (5 papers), Mechanical and Optical Resonators (4 papers), stochastic dynamics and bifurcation (4 papers), Machine Learning in Materials Science (3 papers), Complex Network Analysis Techniques (1 paper), Nonlinear Photonic Systems (1 paper) and Complex Systems and Time Series Analysis (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (168 citations), Computer Networks and Communications (278 citations), Cognitive Neuroscience (207 citations), Materials Chemistry (169 citations) and Electrical and Electronic Engineering (137 citations). Tae-Wook Ko has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Bard Ermentrout, Hie‐Tae Moon, Hyunju Chang, Sungwon Lee, Hyun Woo Kim, Jino Im, Pan‐Jun Kim, Hawoong Jeong, Joseph Lee and Yasser Iturria‐Medina. Their work appears in journals such as Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Scientific Reports, Chaos An Interdisciplinary Journal of Nonlinear Science, npj Computational Materials and Physica D Nonlinear Phenomena.

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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