World's Best Scientists 2026 revealed!
Joongheon Kim

Joongheon Kim

D-Index & Metrics

Computer Science

D-Index
34
Citations
4551
World Ranking
12228
National Ranking
157

Joongheon Kim publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Joongheon Kim sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 304 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Joongheon Kim D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Joongheon Kim sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Joongheon Kim is affiliated with Korea University in South Korea and has a substantial record of contributions in the fields of computer science and engineering. Their research primarily encompasses artificial intelligence, computer networks and communications, electrical and electronic engineering, aerospace engineering, and computer vision and pattern recognition.

The scientist's research extensively covers several main topics, including:

  • UAV Applications and Optimization
  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Privacy-Preserving Technologies in Data
  • Advanced MIMO Systems Optimization
  • Neural Networks and Reservoir Computing
  • Blockchain Technology Applications and Security

Kim has published numerous papers, with a variety of recent contributions highlighting developments in multi-agent systems, reinforcement learning, and IoT networks. Selected recent works include:

  • "Cooperative Multiagent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control" (2022), published in IEEE Transactions on Industrial Informatics
  • "Multiagent DDPG-Based Deep Learning for Smart Ocean Federated Learning IoT Networks" (2020), published in IEEE Internet of Things Journal
  • "Orchestrated Scheduling and Multi-Agent Deep Reinforcement Learning for Cloud-Assisted Multi-UAV Charging Systems" (2021), published in IEEE Transactions on Vehicular Technology
  • "Multiscale LSTM-Based Deep Learning for Very-Short-Term Photovoltaic Power Generation Forecasting in Smart City Energy Management" (2020), published in IEEE Systems Journal
  • "Distributed deep reinforcement learning for autonomous aerial eVTOL mobility in drone taxi applications" (2021), published in ICT Express

Frequent collaborators include Soyi Jung, Soohyun Park, Won Joon Yun, Hankyul Baek, and Jihong Park. These coauthors have worked with Kim on a significant number of papers, reinforcing collaborative efforts within the research community.

Kim's work is regularly published in well-established venues within their disciplines. The most common publication outlets are:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • IEEE Access
  • IEEE Transactions on Vehicular Technology
  • IEEE Transactions on Mobile Computing

The merging of advanced machine learning methods such as deep reinforcement learning with practical applications like UAV control, federated learning IoT networks, and smart energy management defines a distinct part of Kim's recent research trajectory. This profile underlines a multidisciplinary approach intersecting artificial intelligence, communications, and aerospace technologies.

Best Publications

  • Energy-efficient rate-adaptive GPS-based positioning for smartphones

    Jeongyeup Paek;Joongheon Kim;Ramesh Govindan

  • Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications

    Jihong Park;Sumudu Samarakoon;Anis Elgabli;Joongheon Kim

  • Cooperative Multiagent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control

    Unknown

  • Quality-Aware Streaming and Scheduling for Device-to-Device Video Delivery

    Joongheon Kim;Giuseppe Caire;Andreas F. Molisch

  • Toward Characterizing Blockchain-Based Cryptocurrencies for Highly Accurate Predictions

    Muhammad Saad;Jinchun Choi;DaeHun Nyang;Joongheon Kim

  • A Tutorial on Quantum Convolutional Neural Networks (QCNN)

    Seunghyeok Oh;Jaeho Choi;Joongheon Kim

  • Cooperative Management for PV/ESS-Enabled Electric Vehicle Charging Stations: A Multiagent Deep Reinforcement Learning Approach

    MyungJae Shin;Dae-Hyun Choi;Joongheon Kim

  • Residential Demand Response for Renewable Energy Resources in Smart Grid Systems

    Laihyuk Park;Yongwoon Jang;Sungrae Cho;Joongheon Kim

  • Multiagent DDPG-Based Deep Learning for Smart Ocean Federated Learning IoT Networks

    Dohyun Kwon;Joohyung Jeon;Soohyun Park;Joongheon Kim

  • Energy-Efficient Mobile Charging for Wireless Power Transfer in Internet of Things Networks

    Woongsoo Na;Junho Park;Cheol Lee;Kyoungjun Park

  • Movement-Aware Vertical Handoff of WLAN and Mobile WiMAX for Seamless Ubiquitous Access

    Wonjun Lee;Eunkyo Kim;Joongheon Kim;Inkyu Lee

  • Fast millimeter-wave beam training with receive beamforming

    Joongheon Kim;Andreas F. Molisch

  • Quantum Neural Networks: Concepts, Applications, and Challenges

    Yunseok Kwak;Won Joon Yun;Soyi Jung;Joongheon Kim

  • Orchestrated Scheduling and Multi-Agent Deep Reinforcement Learning for Cloud-Assisted Multi-UAV Charging Systems

    Soyi Jung;Won Joon Yun;MyungJae Shin;Joongheon Kim

  • A Tutorial on Quantum Approximate Optimization Algorithm (QAOA): Fundamentals and Applications

    Jaeho Choi;Joongheon Kim

  • Multiscale LSTM-Based Deep Learning for Very-Short-Term Photovoltaic Power Generation Forecasting in Smart City Energy Management

    Dohyun Kim;Dohyun Kwon;Laihyuk Park;Joongheon Kim

  • Internet of Things for Smart Manufacturing System: Trust Issues in Resource Allocation

    Seohyeon Jeong;Woongsoo Na;Joongheon Kim;Sungrae Cho

  • Mempool optimization for Defending Against DDoS Attacks in PoW-based Blockchain Systems

    Muhammad Saad;Laurent Njilla;Charles Kamhoua;Joongheon Kim

  • Effect of localized optimal clustering for reader anti-collision in RFID networks: fairness aspects to the readers

    Joongheon Kim;Wonjun Lee;Jieun Yu;Jihoon Myung

  • Pre-coding method for spatial multiplexing in multiple input and output system

    Beom Jin Jeon;Joong Heon Kim;Alexander Flaksman;Alexey Rubtsov

  • Joint Scalable Coding and Routing for 60 GHz Real-Time Live HD Video Streaming Applications

    Joongheon Kim;Yafei Tian;S. Mangold;A. F. Molisch

  • Auction-Based Charging Scheduling With Deep Learning Framework for Multi-Drone Networks

    MyungJae Shin;Joongheon Kim;Marco Levorato

  • Energy-Efficient Dynamic Packet Downloading for Medical IoT Platforms

    Joongheon Kim

  • XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning.

    Myungjae Shin;Chihoon Hwang;Joongheon Kim;Jihong Park

  • Privacy-Sensitive Parallel Split Learning

    Joohyung Jeon;Joongheon Kim

  • Distributed deep reinforcement learning for autonomous aerial eVTOL mobility in drone taxi applications

    Won Joon Yun;Soyi Jung;Joongheon Kim;Jae-Hyun Kim

  • Wireless Video Caching and Dynamic Streaming Under Differentiated Quality Requirements

    Minseok Choi;Joongheon Kim;Jaekyun Moon

  • Securing Heterogeneous IoT With Intelligent DDoS Attack Behavior Learning

    Nhu-Ngoc Dao;Trung V. Phan;Umar Sa’ad;Joongheon Kim

  • Quantum Multiagent Actor–Critic Networks for Cooperative Mobile Access in Multi-UAV Systems

    Unknown

  • Seamless Dynamic Adaptive Streaming in LTE/Wi-Fi Integrated Network under Smartphone Resource Constraints

    Jonghoe Koo;Juheon Yi;Joongheon Kim;Mohammad Ashraful Hoque

  • Intelligent Active Queue Management for Stabilized QoS Guarantees in 5G Mobile Networks

    Soyi Jung;Joongheon Kim;Jae-Hyun Kim

Frequent Co-Authors

Wonjun Lee
Wonjun Lee Korea University
David Mohaisen
David Mohaisen University of Central Florida
Andreas F. Molisch
Andreas F. Molisch University of Southern California
Jae-Hyun Kim
Jae-Hyun Kim Ajou University
Sungrae Cho
Sungrae Cho Chung-Ang University
Jihong Park
Jihong Park Singapore University of Technology and Design
Mehdi Bennis
Mehdi Bennis University of Oulu
Giuseppe Caire
Giuseppe Caire Technical University of Berlin
Carlos Cordeiro
Carlos Cordeiro Intel (United States)
Sunghyun Choi
Sunghyun Choi Samsung (South Korea)

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