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Joongheon Kim

Joongheon Kim

D-Index & Metrics

Computer Science

D-Index
34
Citations
4551
World Ranking
12230
National Ranking
157

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
Aziz Mohaisen
Aziz Mohaisen University of Central Florida
Andreas F. Molisch
Andreas F. Molisch University of Southern California
Jae-Hyun Kim
Jae-Hyun Kim Ajou University
Mehdi Bennis
Mehdi Bennis University of Oulu
Jihong Park
Jihong Park Singapore University of Technology and Design
Giuseppe Caire
Giuseppe Caire Technical University of Berlin
Carlos Cordeiro
Carlos Cordeiro Intel (United States)
Sunghyun Choi
Sunghyun Choi Samsung (South Korea)
Yeong Min Jang
Yeong Min Jang Kookmin University

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