World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
8391
World Ranking
11033
National Ranking
1361

Overview

Qing Ling is affiliated with Sun Yat-sen University in China and has contributed extensively to the field of computer science, with a focus on artificial intelligence, computer networks and communications, electrical and electronic engineering, computational mechanics, and molecular biology.

Their research spans several main topics, including stochastic gradient optimization techniques, distributed control multi-agent systems, privacy-preserving technologies in data, distributed sensor networks and detection algorithms, sparse and compressive sensing techniques, adversarial robustness in machine learning, and random matrices and applications.

Qing Ling has authored multiple papers published in notable venues. Key recent publications include:

  • Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks (2020, IEEE Transactions on Signal Processing)
  • Deep Adversarial Data Augmentation for Extremely Low Data Regimes (2020, IEEE Transactions on Circuits and Systems for Video Technology)
  • HierTrain: Fast Hierarchical Edge AI Learning With Hybrid Parallelism in Mobile-Edge-Cloud Computing (2020, IEEE Open Journal of the Communications Society)
  • Byzantine-Resilient Decentralized Stochastic Optimization With Robust Aggregation Rules (2023, IEEE Transactions on Signal Processing)
  • Real-Time OFDM Signal Modulation Classification Based on Deep Learning and Software-Defined Radio (2021, IEEE Communications Letters)

Regarding collaboration, Qing Ling has frequent co-authors including:

  • Zhaoxian Wu
  • Tianyi Chen
  • Hua-Long Zhu
  • Wei Chang
  • Weiyu Li

Their publications are often featured in well-regarded venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Signal Processing
  • IEEE Transactions on Signal and Information Processing over Networks

Qing Ling's work contributes primarily to advancing knowledge and techniques in computer science, particularly in optimization methods, distributed systems, and security-related aspects of machine learning and signal processing.

Best Publications

  • EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization

    Wei Shi;Qing Ling;Gang Wu;Wotao Yin

  • On the Linear Convergence of the ADMM in Decentralized Consensus Optimization

    Wei Shi;Qing Ling;Kun Yuan;Gang Wu

  • On the Convergence of Decentralized Gradient Descent

    Kun Yuan;Qing Ling;Wotao Yin

  • RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets

    Liping Li;Wei Xu;Tianyi Chen;Georgios B. Giannakis

  • A Proximal Gradient Algorithm for Decentralized Composite Optimization

    Wei Shi;Qing Ling;Gang Wu;Wotao Yin

  • Decentralized Dynamic Optimization Through the Alternating Direction Method of Multipliers

    Qing Ling;Alejandro Ribeiro

  • An Online Convex Optimization Approach to Proactive Network Resource Allocation

    Tianyi Chen;Qing Ling;Georgios B. Giannakis

  • D3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images

    Zhangyang Wang;Ding Liu;Shiyu Chang;Qing Ling

  • Decentralized Sparse Signal Recovery for Compressive Sleeping Wireless Sensor Networks

    Qing Ling;Zhi Tian

  • DLM: Decentralized Linearized Alternating Direction Method of Multipliers

    Qing Ling;Wei Shi;Gang Wu;Alejandro Ribeiro

  • Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks

    Zhaoxian Wu;Qing Ling;Tianyi Chen;Georgios B. Giannakis

  • Network Newton Distributed Optimization Methods

    Aryan Mokhtari;Qing Ling;Alejandro Ribeiro

  • Decentralized Consensus Optimization With Asynchrony and Delays

    Tianyu Wu;Kun Yuan;Qing Ling;Wotao Yin

  • DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers

    Aryan Mokhtari;Wei Shi;Qing Ling;Alejandro Ribeiro

  • A Decentralized Second-Order Method with Exact Linear Convergence Rate for Consensus Optimization

    Aryan Mokhtari;Wei Shi;Qing Ling;Alejandro Ribeiro

  • Decentralized learning for wireless communications and networking

    Georgios B. Giannakis;Qing Ling;Gonzalo Mateos;Ioannis D. Schizas

  • Decentralized quadratically approximated alternating direction method of multipliers

    Aryan Mokhtari;Wei Shi;Qing Ling;Alejandro Ribeiro

  • Localized Structural Health Monitoring Using Energy-Efficient Wireless Sensor Networks

    Qing Ling;Zhi Tian;Yuejun Yin;Yue Li

  • DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification

    Xiaofeng Zhang;Zhangyang Wang;Dong Liu;Qing Ling

  • Conditional Augmentation for Aspect Term Extraction via Masked Sequence-to-Sequence Generation

    Kun Li;Chengbo Chen;Xiaojun Quan;Qing Ling

  • Learning deep l0 encoders

    Zhangyang Wang;Qing Ling;Thomas S Huang

Frequent Co-Authors

Zhi Tian
Zhi Tian George Mason University
Alejandro Ribeiro
Alejandro Ribeiro University of Pennsylvania
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Wotao Yin
Wotao Yin Alibaba Group (China)
Georgios B. Giannakis
Georgios B. Giannakis University of Minnesota
Aryan Mokhtari
Aryan Mokhtari The University of Texas at Austin
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Houqiang Li
Houqiang Li University of Science and Technology of China
Shiyu Chang
Shiyu Chang University of California, Santa Barbara
Anthony Man-Cho So
Anthony Man-Cho So Chinese University of Hong Kong

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