World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
11518
World Ranking
5301
National Ranking
72

Overview

Han Yu is affiliated with Nanyang Technological University in Singapore and has contributed extensively to the field of computer science, with a specialization in artificial intelligence and its related subfields.

The scientist's research spans a variety of subfields, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Molecular Biology
  • Electrical and Electronic Engineering

Han Yu's work covers key topics within these areas, focusing on:

  • Privacy-Preserving Technologies in Data
  • Cryptography and Data Security
  • Mobile Crowdsensing and Crowdsourcing
  • Stochastic Gradient Optimization Techniques
  • Advanced Graph Neural Networks
  • Domain Adaptation and Few-Shot Learning
  • Blockchain Technology Applications and Security

Frequent coauthors include Qiang Yang, Yang Liu, Dusit Niyato, Tianjian Chen, and Chunyan Miao, indicating strong collaborative ties within the research community.

Han Yu has published extensively across multiple venues. The most frequent publication platforms are:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Internet of Things Journal
  • IEEE Transactions on Neural Networks and Learning Systems
  • Knowledge-Based Systems

Notable recent papers authored or coauthored by Han Yu include:

  • A systematic literature review of the capabilities and performance metrics of supply chain resilience, 2020, International Journal of Production Research
  • Privacy and Robustness in Federated Learning: Attacks and Defenses, 2022, IEEE Transactions on Neural Networks and Learning Systems
  • FedVision: An Online Visual Object Detection Platform Powered by Federated Learning, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Threats to Federated Learning: A Survey, 2020, arXiv (Cornell University)
  • Towards Out-Of-Distribution Generalization: A Survey, 2021, arXiv (Cornell University)

In addition to journal and conference papers, Han Yu has contributed to scholarly books, including "Federated Learning," published in 2020 by Morgan & Claypool Publishers.

Best Publications

  • Advances and Open Problems in Federated Learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • Advances and open problems in federated learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • Visual Domain Adaptation with Manifold Embedded Distribution Alignment

    Jindong Wang;Wenjie Feng;Yiqiang Chen;Han Yu

  • A Survey of Zero-Shot Learning: Settings, Methods, and Applications

    Wei Wang;Vincent W. Zheng;Han Yu;Chunyan Miao

  • Privacy and Robustness in Federated Learning: Attacks and Defenses.

    Lingjuan Lyu;Han Yu;Xingjun Ma;Lichao Sun

  • A Survey of Trust and Reputation Management Systems in Wireless Communications

    Han Yu;Zhiqi Shen;Chunyan Miao;Cyril Leung

  • Transfer Learning with Dynamic Distribution Adaptation

    Jindong Wang;Yiqiang Chen;Wenjie Feng;Han Yu

  • Threats to Federated Learning

    Lingjuan Lyu;Han Yu;Jun Zhao;Qiang Yang

  • FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

    Yang Liu;Anbu Huang;Yun Luo;He Huang

  • A Survey of Multi-Agent Trust Management Systems

    Han Yu;Zhiqi Shen;Cyril Leung;Chunyan Miao

  • Threats to Federated Learning: A Survey

    Lingjuan Lyu;Han Yu;Qiang Yang

  • Federated Learning

    Unknown

  • Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach

    Jiawen Kang;Zehui Xiong;Dusit Niyato;Han Yu

  • Building ethics into artificial intelligence

    Han Yu;Zhiqi Shen;Chunyan Miao;Cyril Leung;Cyril Leung

  • Towards Out-Of-Distribution Generalization: A Survey

    Zheyan Shen;Jiashuo Liu;Yue He;Xingxuan Zhang

  • Towards Fair and Privacy-Preserving Federated Deep Models

    Lingjuan Lyu;Jiangshan Yu;Karthik Nandakumar;Yitong Li

  • A Fairness-aware Incentive Scheme for Federated Learning

    Han Yu;Zelei Liu;Yang Liu;Tianjian Chen

  • Federated Learning

    Unknown

  • Collaborative Fairness in Federated Learning

    Lingjuan Lyu;Xinyi Xu;Qian Wang;Han Yu

  • A study on factors affecting service quality and loyalty intention in mobile banking

    Qingji Zhou;Qingji Zhou;Fong Jie Lim;Han Yu;Gaoqian Xu

  • Deep Model for Dropout Prediction in MOOCs

    Wei Wang;Han Yu;Chunyan Miao

  • Easy Transfer Learning By Exploiting Intra-Domain Structures

    Jindong Wang;Yiqiang Chen;Han Yu;Meiyu Huang

  • Mitigating Herding in Hierarchical Crowdsourcing Networks.

    Han Yu;Chunyan Miao;Cyril Leung;Cyril Leung;Yiqiang Chen;Yiqiang Chen

  • Towards a trust aware cognitive radio architecture

    Tao Qin;Han Yu;Cyril Leung;Zhiqi Shen

Frequent Co-Authors

Chunyan Miao
Chunyan Miao Nanyang Technological University
Zhiqi Shen
Zhiqi Shen Nanyang Technological University
Cyril Leung
Cyril Leung University of British Columbia
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Yiqiang Chen
Yiqiang Chen Chinese Academy of Sciences
Pär Nordlund
Pär Nordlund Karolinska Institute
Jun Lin
Jun Lin Chinese Academy of Sciences
Victor Lesser
Victor Lesser University of Massachusetts Amherst
Dusit Niyato
Dusit Niyato Nanyang Technological University
Bo An
Bo An Nanyang Technological University

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