World's Best Scientists 2026 revealed!

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Computer Science

D-Index
44
Citations
10052
World Ranking
7474
National Ranking
984

Overview

Aoying Zhou is affiliated with East China Normal University in China. Their research primarily spans the fields of computer science and engineering, with significant contributions in related subfields including computer networks and communications, information systems, artificial intelligence, electrical and electronic engineering, and aerospace engineering.

Their work frequently appears in prominent venues such as arXiv (Cornell University), IEEE Transactions on Mobile Computing, IEEE Internet of Things Journal, IEEE Transactions on Services Computing, and SSRN Electronic Journal.

Aoying Zhou's recent publications include:

  • Dependency-Aware Task Scheduling in Vehicular Edge Computing, 2020, IEEE Internet of Things Journal
  • Profit-Aware Edge Server Placement, 2021, IEEE Internet of Things Journal
  • A Cloud-Edge Collaboration Framework for Cognitive Service, 2020, IEEE Transactions on Cloud Computing
  • QoS Driven Task Offloading with Statistical Guarantee in Mobile Edge Computing, 2020, IEEE Transactions on Mobile Computing
  • Edgence: A blockchain-enabled edge-computing platform for intelligent IoT-based dApps, 2020, China Communications

The scientist's research topics cover a range of areas including:

  • IoT and Edge/Fog Computing
  • Age of Information Optimization
  • Cloud Computing and Resource Management
  • Satellite Communication Systems
  • Privacy-Preserving Technologies in Data
  • Blockchain Technology Applications and Security
  • IoT Networks and Protocols

Aoying Zhou has collaborated frequently with a number of coauthors, such as Shangguang Wang, Xiao Ma, Mengwei Xu, Qibo Sun, and Wenwu Zhao. These collaborations have yielded a substantial body of research output.

Best Publications

  • Density-Based Clustering over an Evolving Data Stream with Noise.

    Feng Cao;Martin Ester;Weining Qian;Aoying Zhou

  • Security and Privacy in Cloud Computing: A Survey

    Minqi Zhou;Rong Zhang;Wei Xie;Weining Qian

  • PeerDB: a P2P-based system for distributed data sharing

    W.S. Ng;B.C. Ooi;K.-L. Tan;Aoying Zhou

  • BiNE: Bipartite Network Embedding

    Ming Gao;Leihui Chen;Xiangnan He;Aoying Zhou

  • False positive or false negative: mining frequent itemsets from high speed transactional data streams

    Jeffery Xu Yu;Zhihong Chong;Hongjun Lu;Aoying Zhou

  • Tracking clusters in evolving data streams over sliding windows

    Aoying Zhou;Feng Cao;Weining Qian;Cheqing Jin

  • Dynamically maintaining frequent items over a data stream

    Cheqing Jin;Weining Qian;Chaofeng Sha;Jeffrey X. Yu

  • VBI-Tree: A Peer-to-Peer Framework for Supporting Multi-Dimensional Indexing Schemes

    H.V. Jagadish;Beng Chin Ooi;Quang Hieu Vu;Rong Zhang

  • Supporting multi-dimensional range queries in peer-to-peer systems

    Yanfeng Shu;Beng Chin Ooi;Kian-Lee Tan;Aoying Zhou

  • A retrospective of knowledge graphs

    Jihong Yan;Chengyu Wang;Wenliang Cheng;Ming Gao

  • Finding Top-k Shortest Paths with Diversity

    Huiping Liu;Cheqing Jin;Bin Yang;Aoying Zhou

  • Query processing of massive trajectory data based on mapreduce

    Qiang Ma;Bin Yang;Weining Qian;Aoying Zhou

  • M-kernel merging: towards density estimation over data streams

    Aoying Zhou;Zhiyuan Cai;Li Wei;Weining Qian

  • A false negative approach to mining frequent itemsets from high speed transactional data streams

    Jeffrey Xu Yu;Zhihong Chong;Hongjun Lu;Zhenjie Zhang

  • Bloom filter-based XML packets filtering for millions of path queries

    Xueqing Gong;Weining Qian;Ying Yan;Aoying Zhou

  • Towards online anti-opinion spam: spotting fake reviews from the review sequence

    Yuming Lin;Tao Zhu;Hao Wu;Jingwei Zhang

  • Finding centric local outliers in categorical/numerical spaces

    Jeffrey Xu Yu;Weining Qian;Hongjun Lu;Aoying Zhou

  • Distributed Data Stream Clustering: A Fast EM-based Approach

    Aoying Zhou;Feng Cao;Ying Yan;Chaofeng Sha

  • Knowledge Engineering with Big Data

    Xindong Wu;Huanhuan Chen;Gongqing Wu;Jun Liu

  • Approaches for scaling DBSCAN algorithm to large spatial databases

    Unknown

  • False Positive or False Negative

    Jeffrey Xu Yu;Zhihong Chong;Hongjun Lu;Aoying Zhou

Frequent Co-Authors

Shuigeng Zhou
Shuigeng Zhou Fudan University
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Kian-Lee Tan
Kian-Lee Tan National University of Singapore
Beng Chin Ooi
Beng Chin Ooi National University of Singapore
Bin Yang
Bin Yang Aalborg University
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology
Wilfred Ng
Wilfred Ng Hong Kong University of Science and Technology
Hongjun Lu
Hongjun Lu Hong Kong University of Science and Technology
Heng Tao Shen
Heng Tao Shen University of Electronic Science and Technology of China
Jianping Fan
Jianping Fan University of North Carolina at Charlotte

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