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Zhifeng Zhao

Zhifeng Zhao

D-Index & Metrics

Computer Science

D-Index
33
Citations
5504
World Ranking
12557
National Ranking
1541

Overview

Zhifeng Zhao is a researcher affiliated with Zhejiang Lab in China, with a significant body of work primarily focused on computer science and engineering disciplines.

Their research spans several main fields of study, including:

  • Computer Science
  • Engineering

Within these broad fields, their work addresses a variety of subfields of study such as:

  • Artificial Intelligence
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition

Zhifeng Zhao's research covers several main topics, highlighting a focus on both theoretical and applied aspects, including:

  • Wireless Signal Modulation Classification
  • Advanced Fluorescence Microscopy Techniques
  • Distributed Control Multi-Agent Systems
  • Privacy-Preserving Technologies in Data
  • Photoacoustic and Ultrasonic Imaging
  • Software-Defined Networks and 5G
  • Opportunistic and Delay-Tolerant Networks

The researcher has contributed to the academic community through publications in various venues, with frequent appearances in:

  • arXiv (Cornell University)
  • IEEE Transactions on Vehicular Technology
  • IEEE Transactions on Mobile Computing
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Methods

Among several published papers, notable examples include:

  • Intelligent Computing: The Latest Advances, Challenges, and Future, 2023, Intelligent Computing
  • Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised denoising, 2021, Nature Methods
  • Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit, 2022, Nature Biotechnology
  • The LSTM-Based Advantage Actor-Critic Learning for Resource Management in Network Slicing With User Mobility, 2020, IEEE Communications Letters
  • Semantic Communication With Adaptive Universal Transformer, 2021, IEEE Wireless Communications Letters

Their collaborative work involves frequent co-authors such as:

  • Rongpeng Li
  • Honggang Zhang
  • Jiamin Wu
  • Chenghui Peng
  • Jian Wu

Best Publications

  • Intelligent 5G: When Cellular Networks Meet Artificial Intelligence

    Rongpeng Li;Zhifeng Zhao;Xuan Zhou;Guoru Ding

  • Deep Learning with Long Short-Term Memory for Time Series Prediction

    Yuxiu Hua;Zhifeng Zhao;Rongpeng Li;Xianfu Chen

  • Deep Reinforcement Learning for Resource Management in Network Slicing

    Rongpeng Li;Zhifeng Zhao;Qi Sun;Chih-Lin I

  • AI-Based Two-Stage Intrusion Detection for Software Defined IoT Networks

    Jiaqi Li;Zhifeng Zhao;Rongpeng Li;Honggang Zhang

  • GAN-Powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

    Yuxiu Hua;Rongpeng Li;Zhifeng Zhao;Xianfu Chen

  • TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

    Rongpeng Li;Zhifeng Zhao;Xianfu Chen;Jacques Palicot

  • The Learning and Prediction of Application-Level Traffic Data in Cellular Networks

    Rongpeng Li;Zhifeng Zhao;Jianchao Zheng;Chengli Mei

  • The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice

    Rongpeng Li;Zhifeng Zhao;Xuan Zhou;Jacques Palicot

  • Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach

    Xianfu Chen;Zhifeng Zhao;Celimuge Wu;Mehdi Bennis

  • Rethinking Modern Communication from Semantic Coding to Semantic Communication

    Kun Lu;Qingyang Zhou;Rongpeng Li;Zhifeng Zhao

  • The LSTM-Based Advantage Actor-Critic Learning for Resource Management in Network Slicing With User Mobility

    Rongpeng Li;Chujie Wang;Zhifeng Zhao;Rongbin Guo

  • Semantic Communication with Adaptive Universal Transformer

    Qingyang Zhou;Rongpeng Li;Zhifeng Zhao;Chenghui Peng

  • Deep Reinforcement Learning With Discrete Normalized Advantage Functions for Resource Management in Network Slicing

    Chen Qi;Yuxiu Hua;Rongpeng Li;Zhifeng Zhao

  • Stochastic Power Adaptation with Multiagent Reinforcement Learning for Cognitive Wireless Mesh Networks

    Xianfu Chen;Zhifeng Zhao;Honggang Zhang

  • Semantics-Empowered Communications: A Tutorial-Cum-Survey

    Unknown

  • NetGPT: An AI-Native Network Architecture for Provisioning Beyond Personalized Generative Services

    Unknown

  • Machine learning-based IDS for software-defined 5G network

    Jiaqi Li;Zhifeng Zhao;Rongpeng Li

  • Graph Attention Network-Based Multi-Agent Reinforcement Learning for Slicing Resource Management in Dense Cellular Network

    Yan Shao;Rongpeng Li;Bing Hu;Yingxiao Wu

  • Cooperative Multilayer Edge Caching in Integrated Satellite-Terrestrial Networks

    Xiangming Zhu;Chunxiao Jiang;Linling Kuang;Zhifeng Zhao

  • Towards green wireless access networks

    Tao Chen;Honggang Zhang;Zhifeng Zhao;Xianfu Chen

  • The predictability of cellular networks traffic

    Xuan Zhou;Zhifeng Zhao;Rongpeng Li;Yifan Zhou

  • GAN-Based Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

    Yuxiu Hua;Rongpeng Li;Zhifeng Zhao;Honggang Zhang

  • Deep Reinforcement Learning for Resource Management in Network Slicing

    Rongpeng Li;Zhifeng Zhao;Qi Sun;Chi-Lin I

Frequent Co-Authors

Honggang Zhang
Honggang Zhang Zhejiang University
Tao Chen
Tao Chen VTT Technical Research Centre of Finland
Mehdi Bennis
Mehdi Bennis University of Oulu
Jon Crowcroft
Jon Crowcroft University of Cambridge
Chunxiao Jiang
Chunxiao Jiang Tsinghua University
Yusheng Ji
Yusheng Ji National Institute of Informatics
David Grace
David Grace University of York
Chenyang Yang
Chenyang Yang Beihang University
Zhu Han
Zhu Han University of Houston
Hang Liu
Hang Liu Wuhan University of Technology

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