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D-Index & Metrics

Electronics and Electrical Engineering

D-Index
55
Citations
14545
World Ranking
2146
National Ranking
71

Overview

Ming Ding is affiliated with the Commonwealth Scientific and Industrial Research Organisation in Australia. Their work spans a broad range of topics primarily situated within computer science and engineering.

Their research contributions are notably concentrated in the subfields of artificial intelligence, electrical and electronic engineering, computer networks and communications, computer vision and pattern recognition, and aerospace engineering.

The main topics Ming Ding has addressed include:

  • Privacy-Preserving Technologies in Data
  • Cryptography and Data Security
  • Advanced MIMO Systems Optimization
  • Blockchain Technology Applications and Security
  • IoT and Edge/Fog Computing
  • Cooperative Communication and Network Coding
  • Adversarial Robustness in Machine Learning

Frequent collaborators throughout Ming Ding's career have been:

  • Jun Li
  • Kang Wei
  • H. Vincent Poor
  • Chuan Ma
  • Bo Liu

Ming Ding has published extensively with notable presence in several publication venues. These include:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • IEEE Transactions on Information Forensics and Security
  • IEEE Transactions on Vehicular Technology
  • IEEE Transactions on Mobile Computing

Among recent publications are:

  • Federated Learning With Differential Privacy: Algorithms and Performance Analysis, 2020, IEEE Transactions on Information Forensics and Security
  • 6G Internet of Things: A Comprehensive Survey, 2021, IEEE Internet of Things Journal
  • Federated Learning for Smart Healthcare: A Survey, 2022, ACM Computing Surveys
  • Blockchain for 5G and beyond networks: A state of the art survey, 2020, Journal of Network and Computer Applications
  • When Machine Learning Meets Privacy, 2021, ACM Computing Surveys

In addition to journal articles, Ming Ding has contributed to book literature, including the publication:

  • Fundamentals of Ultra-Dense Wireless Networks, 2022, Cambridge University Press

Best Publications

  • Federated Learning for Internet of Things: A Comprehensive Survey

    Dinh C. Nguyen;Ming Ding;Pubudu N. Pathirana;Aruna Seneviratne

  • Federated Learning With Differential Privacy: Algorithms and Performance Analysis

    Kang Wei;Jun Li;Ming Ding;Chuan Ma

  • Survey on UAV Cellular Communications: Practical Aspects, Standardization Advancements, Regulation, and Security Challenges

    Azade Fotouhi;Haoran Qiang;Ming Ding;Mahbub Hassan

  • Towards 1 Gbps/UE in Cellular Systems: Understanding Ultra-Dense Small Cell Deployments

    David Lopez-Perez;Ming Ding;Holger Claussen;Amir H. Jafari

  • Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems

    Dinh C. Nguyen;Pubudu N. Pathirana;Ming Ding;Aruna Seneviratne

  • Blockchain for 5G and beyond networks: A state of the art survey

    Dinh C. Nguyen;Pubudu N. Pathirana;Ming Ding;Aruna Seneviratne

  • The Impact of Adverse Weather Conditions on Autonomous Vehicles: How Rain, Snow, Fog, and Hail Affect the Performance of a Self-Driving Car

    Shizhe Zang;Ming Ding;David Smith;Paul Tyler

  • When Machine Learning Meets Privacy: A Survey and Outlook

    Bo Liu;Ming Ding;Sina Shaham;Wenny Rahayu

  • Performance Impact of LoS and NLoS Transmissions in Dense Cellular Networks

    Ming Ding;Peng Wang;David Lopez-Perez;Guoqiang Mao

  • On Safeguarding Privacy and Security in the Framework of Federated Learning

    Chuan Ma;Jun Li;Ming Ding;Howard H. Yang

  • Path Planning for UAV-Mounted Mobile Edge Computing With Deep Reinforcement Learning

    Qian Liu;Long Shi;Linlin Sun;Jun Li

  • Privacy-Preserved Task Offloading in Mobile Blockchain With Deep Reinforcement Learning

    Dinh C. Nguyen;Pubudu N. Pathirana;Ming Ding;Aruna Seneviratne

  • Integration of Blockchain and Cloud of Things: Architecture, Applications and Challenges

    Dinh C. Nguyen;Pubudu N. Pathirana;Ming Ding;Aruna Seneviratne

  • Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey

    Dinh C. Nguyen;Ming Ding;Pubudu N. Pathirana;Aruna Seneviratne

  • When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm.

    Chuan Ma;Jun Li;Ming Ding;Long Shi

  • Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective

    Dinh C. Nguyen;Peng Cheng;Ming Ding;David Lopez-Perez

  • BEdgeHealth: A Decentralized Architecture for Edge-Based IoMT Networks Using Blockchain

    Dinh C. Nguyen;Pubudu N. Pathirana;Ming Ding;Aruna Seneviratne

  • Optimal Base Station Antenna Downtilt in Downlink Cellular Networks

    Junnan Yang;Ming Ding;Guoqiang Mao;Zihuai Lin

  • Transmission method, reception method, base station, and user equipment

    チャン,ヤンギュ;Yang-Gyu Chang;リュ,レンマオ;Renmao Liu

  • Enhancing Cellular Communications for UAVs via Intelligent Reflective Surface

    Dong Ma;Ming Ding;Mahbub Hassan

  • Flying Drone Base Stations for Macro Hotspots

    Azade Fotouhi;Ming Ding;Mahbub Hassan

  • Information feedback method and system based on space, time and frequency domain, customer equipment and base station

    Yongming Liang;Renmao Liu;Zhongguang Yan;Ming Ding

Frequent Co-Authors

Zihuai Lin
Zihuai Lin University of Sydney
David Lopez-Perez
David Lopez-Perez Universitat Politècnica de València
Guoqiang Mao
Guoqiang Mao Xidian University
Jun Li
Jun Li Nanjing University of Science and Technology
H. Vincent Poor
H. Vincent Poor Princeton University
Xiaohu Ge
Xiaohu Ge Huazhong University of Science and Technology
Branka Vucetic
Branka Vucetic University of Sydney
Giovanni Geraci
Giovanni Geraci Pompeu Fabra University
Yonghui Li
Yonghui Li University of Sydney
Holger Claussen
Holger Claussen Tyndall National Institute

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