World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
6992
World Ranking
8435
National Ranking
1097

Overview

Qingqi Pei is affiliated with Xidian University in China and has an extensive research record primarily in the fields of Computer Science and Engineering. Their body of work includes 208 publications in Computer Science and 107 in Engineering, with a strong focus on several specialized subfields.

Their research spans subfields such as Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, and Information Systems. Within these areas, the main topics covered are centered around Privacy-Preserving Technologies in Data, IoT and Edge/Fog Computing, Blockchain Technology Applications and Security, Vehicular Ad Hoc Networks (VANETs), Traffic Prediction and Management Techniques, Advanced MIMO Systems Optimization, and Anomaly Detection Techniques and Applications.

Qingqi Pei has contributed significantly to well-regarded venues including:

  • IEEE Internet of Things Journal (18 publications)
  • IEEE Transactions on Intelligent Transportation Systems (14 publications)
  • IEEE Transactions on Wireless Communications (7 publications)
  • arXiv (Cornell University) (7 publications)
  • Remote Sensing (5 publications)

Frequent collaborators in Pei's research include Lei Liu (37 joint publications), Chen Chen (37 joint publications), Jie Feng (24 joint publications), Shaohua Wan (17 joint publications), and Ying Ju (14 joint publications).

Recent notable papers by Qingqi Pei include:

  • "Vehicular Edge Computing and Networking: A Survey" published in 2020 in Mobile Networks and Applications
  • "An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System" published in 2020 in IEEE Transactions on Intelligent Transportation Systems
  • "Personalized Federated Learning With Differential Privacy" published in 2020 in IEEE Internet of Things Journal
  • "A Federated Learning Based Privacy-Preserving Smart Healthcare System" published in 2021 in IEEE Transactions on Industrial Informatics
  • "Joint Secure Offloading and Resource Allocation for Vehicular Edge Computing Network: A Multi-Agent Deep Reinforcement Learning Approach" published in 2023 in IEEE Transactions on Intelligent Transportation Systems

The research topics dealt with in these recent papers cover aspects of edge computing, federated learning, privacy, and intelligent transportation systems, consistent with Pei's broader research interests. Through interdisciplinary contributions blending AI, communication networks, and data privacy, their work addresses multiple challenges in emerging technologies related to IoT, vehicular networks, and smart healthcare systems.

Best Publications

  • Vehicular Edge Computing and Networking: A Survey

    Lei Liu;Chen Chen;Qingqi Pei;Sabita Maharjan

  • An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System

    Chen Chen;Bin Liu;Shaohua Wan;Peng Qiao

  • Cooperative Computation Offloading and Resource Allocation for Blockchain-Enabled Mobile-Edge Computing: A Deep Reinforcement Learning Approach

    Jie Feng;F. Richard Yu;Qingqi Pei;Xiaoli Chu

  • Personalized Federated Learning With Differential Privacy

    Rui Hu;Yuanxiong Guo;Hongning Li;Qingqi Pei

  • A Federated Learning based Privacy-preserving Smart Healthcare System

    Jiachun Li;Yan Meng;Lichuan Ma;Suguo Du

  • Joint Secure Offloading and Resource Allocation for Vehicular Edge Computing Network: A Multi-Agent Deep Reinforcement Learning Approach

    Unknown

  • Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing

    Unknown

  • Heterogeneous Computation and Resource Allocation for Wireless Powered Federated Edge Learning Systems

    Unknown

  • Vehicle Selection and Resource Optimization for Federated Learning in Vehicular Edge Computing

    Huizi Xiao;Jun Zhao;Qingqi Pei;Jie Feng

  • Blockchain-Enabled Secure Data Sharing Scheme in Mobile-Edge Computing: An Asynchronous Advantage Actor–Critic Learning Approach

    Lei Liu;Jie Feng;Qingqi Pei;Chen Chen

  • A novel reversible image data hiding scheme based on pixel value ordering and dynamic pixel block partition

    Xiang Wang;Jing Ding;Qingqi Pei

  • Privacy-Preserving Reputation Management for Edge Computing Enhanced Mobile Crowdsensing

    Lichuan Ma;Xuefeng Liu;Qingqi Pei;Yong Xiang

  • Traffic Flow Prediction Based on Deep Learning in Internet of Vehicles

    Chen Chen;Ziye Liu;Shaohua Wan;Jintai Luan

  • Min-Max Cost Optimization for Efficient Hierarchical Federated Learning in Wireless Edge Networks

    Jie Feng;Lei Liu;Qingqi Pei;Keqin Li

  • Joint Optimization of Radio and Computational Resources Allocation in Blockchain-Enabled Mobile Edge Computing Systems

    Jie Feng;F. Richard Yu;Qingqi Pei;Jianbo Du

  • UAV-Assisted Vehicular Edge Computing for the 6G Internet of Vehicles: Architecture, Intelligence, and Challenges

    Jinna Hu;Chen Chen;Lin Cai;Mohammad R. Khosravi

  • Distributed computation offloading method based on deep reinforcement learning in ICV

    Chen Chen;Yuru Zhang;Zheng Wang;Shaohua Wan

  • Dynamic Network Slicing and Resource Allocation in Mobile Edge Computing Systems

    Jie Feng;Qingqi Pei;F. Richard Yu;Xiaoli Chu

  • QoE Fairness Resource Allocation in Digital Twin-Enabled Wireless Virtual Reality Systems

    Unknown

  • A connectivity-aware intersection-based routing in VANETs

    Chen Chen;Chen Chen;Yanan Jin;Qingqi Pei;Ning Zhang

  • Smart-Contract-Based Economical Platooning in Blockchain-Enabled Urban Internet of Vehicles

    Chen Chen;Tingting Xiao;Tie Qiu;Ning Lv

  • Computation Offloading and Resource Allocation for Wireless Powered Mobile Edge Computing With Latency Constraint

    Jie Feng;Qingqi Pei;F. Richard Yu;Xiaoli Chu

  • Secret Key Establishment via RSS Trajectory Matching Between Wearable Devices

    Zi Li;Qingqi Pei;Ian Markwood;Yao Liu

  • Convolutional Neural Networks for forecasting flood process in Internet-of-Things enabled smart city

    Chen Chen;Qiang Hui;Wenxuan Xie;Shaohua Wan

Frequent Co-Authors

Jianfeng Ma
Jianfeng Ma Xidian University
Shaohua Wan
Shaohua Wan University of Electronic Science and Technology of China
Tie Qiu
Tie Qiu Tianjin University
Xinbo Gao
Xinbo Gao Xidian University
Haojin Zhu
Haojin Zhu Shanghai Jiao Tong University
Lina Yao
Lina Yao Commonwealth Scientific and Industrial Research Organisation
Miao Pan
Miao Pan University of Houston
Shui Yu
Shui Yu University of Technology Sydney
F. Richard Yu
F. Richard Yu Carleton University
Xiaoli Chu
Xiaoli Chu University of Sheffield

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