World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8778
World Ranking
6504
National Ranking
869

Overview

An Liu is affiliated with Soochow University in China and has contributed extensively to the field of computer science, with a focus on artificial intelligence, computer networks and communications, signal processing, information systems, and management science and operations research. Their research output includes a significant number of publications across these domains.

Their work covers several main topics, including:

  • Topic Modeling
  • Privacy-Preserving Technologies in Data
  • Advanced Graph Neural Networks
  • Mobile Crowdsensing and Crowdsourcing
  • Natural Language Processing Techniques
  • Data Management and Algorithms
  • Human Mobility and Location-Based Analysis

Notable recent papers by An Liu include:

  • "Secure Crowdsensed Data Trading Based on Blockchain", 2021, IEEE Transactions on Mobile Computing
  • "A graph embedding based model for fine-grained POI recommendation", 2020, Neurocomputing
  • "Personalized Geographical Influence Modeling for POI Recommendation", 2020, IEEE Intelligent Systems
  • "Co-purchaser Recommendation for Online Group Buying", 2020, Data Science and Engineering
  • "Optimization of Microservice Composition Based on Artificial Immune Algorithm Considering Fuzziness and User Preference", 2020, IEEE Access

Frequent coauthors who have collaborated with An Liu include:

  • Lei Zhao
  • Zhixu Li
  • Jianfeng Qu
  • Guanfeng Liu
  • Jiajie Xu

Their publications have appeared in a range of venues, most notably:

  • World Wide Web
  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management
  • Journal of Software Evolution and Process

An Liu has also contributed to book publications, including a book published by Springer Science+Business Media titled "Web and Big Data. APWeb-WAIM 2021 International Workshops".

The breadth of their work demonstrates engagement with both theoretical and applied aspects of computer science, involving methods and systems related to data privacy, graph neural networks, and recommender systems, among other advanced computational topics.

Best Publications

  • A Survey on Fundamental Limits of Integrated Sensing and Communication

    An Liu;Zhe Huang;Min Li;Yubo Wan

  • On the Design of Secure Non-Orthogonal Multiple Access Systems

    Biao He;An Liu;Nan Yang;Vincent K. N. Lau

  • Phase Only RF Precoding for Massive MIMO Systems With Limited RF Chains

    An Liu;Vincent Kin Nang Lau

  • FACTS: A Framework for Fault-Tolerant Composition of Transactional Web Services

    An Liu;Qing Li;Liusheng Huang;Mingjun Xiao

  • FDD Massive MIMO Channel Estimation With Arbitrary 2D-Array Geometry

    Jisheng Dai;An Liu;Vincent K. N. Lau

  • Stochastic Successive Convex Approximation for Non-Convex Constrained Stochastic Optimization

    An Liu;Vincent K. N. Lau;Borna Kananian

  • Energy-Efficient Joint Offloading and Wireless Resource Allocation Strategy in Multi-MEC Server Systems

    Kang Cheng;Yinglei Teng;Weiqi Sun;An Liu

  • Exploiting Base Station Caching in MIMO Cellular Networks: Opportunistic Cooperation for Video Streaming

    An Liu;Vincent Kin Nang Lau

  • Efficient secure similarity computation on encrypted trajectory data

    An Liu;Kai Zhengy;Lu Liz;Guanfeng Liu

  • Cache-Enabled Opportunistic Cooperative MIMO for Video Streaming in Wireless Systems

    An Liu;Vincent K. N. Lau

  • Efficient task assignment in spatial crowdsourcing with worker and task privacy protection

    An Liu;Weiqi Wang;Shuo Shang;Qing Li

  • Mixed-Timescale Precoding and Cache Control in Cached MIMO Interference Network

    An Liu;Vincent K. N. Lau

  • Joint Power and Antenna Selection Optimization in Large Cloud Radio Access Networks

    An Liu;Vincent Lau

  • Analog Gradient Aggregation for Federated Learning Over Wireless Networks: Customized Design and Convergence Analysis

    Huayan Guo;An Liu;Vincent K. N. Lau

  • Successive Localization and Beamforming in 5G mmWave MIMO Communication Systems

    Bingpeng Zhou;An Liu;Vincent Lau

  • Structured Turbo Compressed Sensing for Massive MIMO Channel Estimation Using a Markov Prior

    Lei Chen;An Liu;Xiaojun Yuan

  • Mitosis sequence detection using hidden conditional random fields

    A-A Liu;K. Li;T. Kanade

  • Effective and efficient trajectory outlier detection based on time-dependent popular route

    Jie Zhu;Wei Jiang;An Liu;Guanfeng Liu

  • Hierarchical Interference Mitigation for Massive MIMO Cellular Networks

    An Liu;Vincent Kin Nang Lau

  • Joint Computation Offloading and Resource Allocation for MEC-Enabled IoT Systems With Imperfect CSI

    Jun Wang;Daquan Feng;Shengli Zhang;An Liu

  • Exploiting Burst-Sparsity in Massive MIMO With Partial Channel Support Information

    An Liu;Vincent K. N. Lau;Wei Dai

  • A Declarative Approach to Enhancing the Reliability of BPEL Processes

    An Liu;Qing Li;Liusheng Huang;Mingjun Xiao

Frequent Co-Authors

Vincent K. N. Lau
Vincent K. N. Lau Hong Kong University of Science and Technology
Guanfeng Liu
Guanfeng Liu Macquarie University
Qing Li
Qing Li Hong Kong Polytechnic University
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology
Liusheng Huang
Liusheng Huang University of Science and Technology of China
Xiangliang Zhang
Xiangliang Zhang University of Notre Dame
Yunlong Cai
Yunlong Cai Zhejiang University
Kai Zheng
Kai Zheng University of Electronic Science and Technology of China
Hongzhi Yin
Hongzhi Yin University of Queensland
Wei Yu
Wei Yu University of Toronto

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