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Computer Science

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Citations
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  • 2025 - Research.com Rising Stars Award

Overview

Mingzhe Chen is a researcher affiliated with the University of Miami in the United States, specializing in Engineering and Computer Science. Their work predominantly focuses on Electrical and Electronic Engineering, Artificial Intelligence, and Computer Networks and Communications, with additional contributions to Aerospace and Biomedical Engineering.

The scientist's research covers various advanced topics, including:

  • Privacy-Preserving Technologies in Data
  • Advanced Wireless Communication Technologies
  • Indoor and Outdoor Localization Technologies
  • Wireless Communication Security Techniques
  • Advanced MIMO Systems Optimization
  • UAV Applications and Optimization
  • Cooperative Communication and Network Coding

Mingzhe Chen has published extensively in prominent venues, with frequent contributions to:

  • arXiv (Cornell University)
  • IEEE Transactions on Wireless Communications
  • IEEE Journal on Selected Areas in Communications
  • IEEE Transactions on Mobile Computing
  • IEEE Internet of Things Journal

Some of their recent papers include:

  • "A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks" (2020) IEEE Transactions on Wireless Communications
  • "Energy Efficient Federated Learning Over Wireless Communication Networks" (2020) IEEE Transactions on Wireless Communications
  • "Distributed Learning in Wireless Networks: Recent Progress and Future Challenges" (2021) IEEE Journal on Selected Areas in Communications
  • "Convergence Time Optimization for Federated Learning Over Wireless Networks" (2020) IEEE Transactions on Wireless Communications
  • "Communication-efficient federated learning" (2021) Proceedings of the National Academy of Sciences

The researcher has collaborated frequently with several co-authors, notably:

  • Walid Saad
  • Shuguang Cui
  • Zhaohui Yang
  • H. Vincent Poor
  • Yuchen Liu

Mingzhe Chen has also authored books published by Springer International Publishing, including:

  • "Federated Learning for Wireless Networks" (2021)
  • "Communication Efficient Federated Learning for Wireless Networks" (2024)
  • "Positioning and Sensing Over Wireless Networks" (2025)

Best Publications

  • A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

    Walid Saad;Mehdi Bennis;Mingzhe Chen

  • A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks

    Mingzhe Chen;Zhaohui Yang;Walid Saad;Changchuan Yin

  • Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial

    Mingzhe Chen;Ursula Challita;Walid Saad;Changchuan Yin

  • Energy Efficient Federated Learning Over Wireless Communication Networks

    Zhaohui Yang;Mingzhe Chen;Walid Saad;Choong Seon Hong

  • Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience

    Mingzhe Chen;Mohammad Mozaffari;Walid Saad;Changchuan Yin

  • Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

    Mingzhe Chen;Deniz Gunduz;Kaibin Huang;Walid Saad

  • Convergence Time Optimization for Federated Learning Over Wireless Networks

    Mingzhe Chen;H. Vincent Poor;Walid Saad;Shuguang Cui

  • Energy-Efficient Wireless Communications with Distributed Reconfigurable Intelligent Surfaces

    Zhaohui Yang;Mingzhe Chen;Walid Saad;Wei Xu

  • Communication-efficient federated learning.

    Mingzhe Chen;Mingzhe Chen;Nir Shlezinger;H. Vincent Poor;Yonina C. Eldar

  • Federated Learning for 6G: Applications, Challenges, and Opportunities.

    Zhaohui Yang;Mingzhe Chen;Kai-Kit Wong;H. Vincent Poor

  • Virtual Reality Over Wireless Networks: Quality-of-Service Model and Learning-Based Resource Management

    Mingzhe Chen;Walid Saad;Changchuan Yin

  • Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks

    Mingzhe Chen;Ursula Challita;Walid Saad;Changchuan Yin

  • UVeQFed: Universal Vector Quantization for Federated Learning

    Nir Shlezinger;Mingzhe Chen;Yonina C. Eldar;H. Vincent Poor

  • Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs

    Ursula Challita;Aidin Ferdowsi;Mingzhe Chen;Walid Saad

  • Performance Optimization for Semantic Communications: An Attention-Based Reinforcement Learning Approach

    Unknown

  • Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms

    Tengchan Zeng;Omid Semiari;Mohammad Mozaffari;Mingzhe Chen

  • Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

    Unknown

  • Echo State Networks for Proactive Caching in Cloud-Based Radio Access Networks With Mobile Users

    Mingzhe Chen;Walid Saad;Changchuan Yin;Merouane Debbah

  • Liquid State Machine Learning for Resource and Cache Management in LTE-U Unmanned Aerial Vehicle (UAV) Networks

    Mingzhe Chen;Walid Saad;Changchuan Yin

  • Wireless Communications for Collaborative Federated Learning

    Mingzhe Chen;H. Vincent Poor;Walid Saad;Shuguang Cui

  • 6G White Paper on Machine Learning in Wireless Communication Networks

    Sammad Ali;Walid Saad;Nandana Rajatheva;Kapseok Chang

  • Wireless Communications for Collaborative Federated Learning in the Internet of Things.

    Mingzhe Chen;H. Vincent Poor;Walid Saad;Shuguang Cui

Frequent Co-Authors

Walid Saad
Walid Saad Virginia Tech
H. Vincent Poor
H. Vincent Poor Princeton University
Changchuan Yin
Changchuan Yin Beijing University of Posts and Telecommunications
Shuguang Cui
Shuguang Cui Chinese University of Hong Kong, Shenzhen
Choong Seon Hong
Choong Seon Hong Kyung Hee University
Merouane Debbah
Merouane Debbah Khalifa University
Mehdi Bennis
Mehdi Bennis University of Oulu
Yuanwei Liu
Yuanwei Liu University of Hong Kong
Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science
Nir Shlezinger
Nir Shlezinger Ben-Gurion University of the Negev

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