World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
47
Citations
10227
World Ranking
3179
National Ranking
91

Computer Science

D-Index
53
Citations
14141
World Ranking
4742
National Ranking
28

Jong-Hwan Kim publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Jong-Hwan Kim sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 420 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Jong-Hwan Kim D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Jong-Hwan Kim sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 47 D-Index — 54th percentile

54% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Jong-Hwan Kim is affiliated with the Korea Advanced Institute of Science and Technology in South Korea, focusing on research predominantly in the fields of computer science and engineering. Their work spans a broad range of topics within these disciplines, including computer vision, artificial intelligence, aerospace engineering, food science, and pollution.

The scientist has contributed notably to various specialized subfields, such as:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Aerospace Engineering
  • Food Science
  • Pollution

Research topics that frequently appear in their publications include:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Pesticide Residue Analysis and Safety
  • Robotics and Sensor-Based Localization
  • Advanced Vision and Imaging

Jong-Hwan Kim has collaborated extensively with a number of co-authors, with key frequent collaborators including:

  • Ue-Hwan Kim
  • Jong-Su Seo
  • Yeong-Jin Kim
  • Ji-Young An
  • Yewon Hwang

The scientist's recent papers illustrate an emphasis on applications of artificial intelligence and computer vision in practical scenarios. Some notable recent publications are:

  • Individualized AI Tutor Based on Developmental Learning Networks, 2020, IEEE Access
  • SimVODIS: Simultaneous Visual Odometry, Object Detection, and Instance Segmentation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Convolutional Recurrent Reconstructive Network for Spatiotemporal Anomaly Detection in Solder Paste Inspection, 2020, IEEE Transactions on Cybernetics
  • MarsNet: Multi-Label Classification Network for Images of Various Sizes, 2020, IEEE Access
  • Convolutional Neural Network With Developmental Memory for Continual Learning, 2020, IEEE Transactions on Neural Networks and Learning Systems

Jong-Hwan Kim's research is published widely, especially in venues such as:

  • arXiv (Cornell University)
  • IEEE Access
  • Scientific Reports
  • Zenodo (CERN European Organization for Nuclear Research)
  • Foods

In addition to journal articles, the scientist has contributed to book publications through Springer International Publishing and Springer Nature, with works including:

  • Robot Intelligence Technology and Applications 6, 2022
  • RiTA 2020, 2021

Best Publications

  • Quantum-inspired evolutionary algorithm for a class of combinatorial optimization

    Kuk-Hyun Han;Jong-Hwan Kim

  • Genetic quantum algorithm and its application to combinatorial optimization problem

    Kuk-Hyun Han;Jong-Hwan Kim

  • Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots

    Jong-Min Yang;Jong-Hwan Kim

  • Quantum-inspired evolutionary algorithms with a new termination criterion, H/sub /spl epsi// gate, and two-phase scheme

    Kuk-Hyun Han;Jong-Hwan Kim

  • Parallel quantum-inspired genetic algorithm for combinatorial optimization problem

    Kuk-Hyun Han;Kui-Hong Park;Ci-Ho Lee;Jong-Hwan Kim

  • Evolutionary programming techniques for constrained optimization problems

    Jong-Hwan Kim;Hyun Myung

  • Quick-RRT*: Triangular inequality-based implementation of RRT* with improved initial solution and convergence rate

    In-Bae Jeong;Seung-Jae Lee;Jong-Hwan Kim

  • Adaptive fuzzy-network-based C-measure map-matching algorithm for car navigation system

    Sinn Kim;Jong-Hwan Kim

  • A real-time limit-cycle navigation method for fast mobile robots and its application to robot soccer

    Dong-Han Kim;Jong-Hwan Kim

  • Effective Background Model-Based RGB-D Dense Visual Odometry in a Dynamic Environment

    Deok-Hwa Kim;Jong-Hwan Kim

  • A two-layered fuzzy logic controller for systems with deadzones

    Jong-Hwan Kim;Jong-Hwan Park;Seon-Woo Lee;E.K.P. Chong

  • Fuzzy precompensation of PID controllers

    Jong-Hwan Kim;Seon-Woo Lee;Kwang-Choon Kim;E.K.P. Chong

  • Sliding Mode Motion Control of Nonholonomic Mobile Robots

    Jung-Min Yang;Jong-Hwan Kim

  • Modular Q-learning based multi-agent cooperation for robot soccer

    Kui-Hong Park;Yong-Jae Kim;Jong-Hwan Kim

  • The geometrical learning of binary neural networks

    J.H. Kim;Sung-Kwon Park

  • Quantum-inspired Multiobjective Evolutionary Algorithm for Multiobjective 0/1 Knapsack Problems

    Yehoon Kim;Jong-Hwan Kim;Kuk-Hyun Han

  • A two-step circle detection algorithm from the intersecting chords

    Heung-Soo Kim;Jong-Hwan Kim

  • A cooperative multi-agent system and its real time application to robot soccer

    J.-H. Kim;H.-S. Shim;H.-S. Kim;M.-J. Jung

  • Fuzzy precompensated PID controllers

    Jong-Hwan Kim;Kwang-Choon Kim;E.K.P. Chong

  • Laser-Based Kinematic Calibration of Robot Manipulator Using Differential Kinematics

    In-Won Park;Bum-Joo Lee;Se-Hyoung Cho;Young-Dae Hong

  • Internet Control Architecture for Internet-Based Personal Robot

    Kuk-Hyun Han;Sinn Kim;Yong-Jae Kim;Jong-Hwan Kim

Frequent Co-Authors

Jee-Hwan Ryu
Jee-Hwan Ryu Korea Advanced Institute of Science and Technology
Edwin K. P. Chong
Edwin K. P. Chong Colorado State University
Shuzhi Sam Ge
Shuzhi Sam Ge National University of Singapore
Moongu Jeon
Moongu Jeon Gwangju Institute of Science and Technology
Dong-Soo Kwon
Dong-Soo Kwon Korea Advanced Institute of Science and Technology
Blake Hannaford
Blake Hannaford University of Washington
Chris Melhuish
Chris Melhuish University of the West of England
Kalyanmoy Deb
Kalyanmoy Deb Michigan State University
Sung-Bae Cho
Sung-Bae Cho Yonsei University
Alexander L. Fradkov
Alexander L. Fradkov Saint Petersburg State University

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Related Online Degrees & Career Pathways

For students interested in Electronics and Electrical Engineering, exploring related online degrees can broaden career options. Many professionals complement their technical skills with management expertise, making accelerated project management degree programs a popular choice. These programs help develop leadership and organizational skills crucial for engineering project oversight.

Those considering flexible learning formats may find online offerings appealing, like bachelor of project management online degrees, which provide a comprehensive education while accommodating busy schedules. This can be especially beneficial for engineers aiming to advance into managerial roles without pausing their careers.

For individuals seeking quicker entry into the workforce, short certificate programs that pay well offer targeted training in high-demand areas, ideal for gaining practical skills without a lengthy commitment. This route can complement a foundation in engineering with specific expertise that boosts employability.

It’s also important to consider personal work style. Many introverts thrive in technical fields, and exploring jobs for introverts that pay well can highlight roles where focused individual work and deep problem-solving are valued, aligning well with engineering disciplines.

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