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Computer Science

D-Index
61
Citations
19398
World Ranking
3019
National Ranking
1480

Overview

Li Zhang is a researcher affiliated with Google in the United States, specializing in the fields of Engineering and Computer Science. Their work predominantly focuses on Electrical and Electronic Engineering, with significant contributions to Computer Networks and Communications, Aerospace Engineering, Information Systems, and Computational Mechanics.

Their research delves into several advanced topics, including:

  • Advanced MIMO Systems Optimization
  • Advanced Wireless Communication Technologies
  • Millimeter-Wave Propagation and Modeling
  • Antenna Design and Analysis
  • Cooperative Communication and Network Coding
  • IoT and Edge/Fog Computing
  • Advanced Antenna and Metasurface Technologies

Li Zhang has published extensively, with a strong presence in leading venues. Frequent publication sites include:

  • IEEE Transactions on Vehicular Technology
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Access
  • IET Communications

Their notable recent papers are:

  • "An Efficient Distributed Task Offloading Scheme for Vehicular Edge Computing Networks" (2021), published in IEEE Transactions on Vehicular Technology
  • "A Super-Wideband and High Isolation MIMO Antenna System Using a Windmill-Shaped Decoupling Structure" (2020), published in IEEE Access
  • "Structured OMP for IRS-Assisted Mmwave Channel Estimation by Exploiting Angular Spread" (2022), published in IEEE Transactions on Vehicular Technology
  • "ByteHTAP" (2022), published in Proceedings of the VLDB Endowment
  • "Resource Allocation for D2D Underlay Communications With Proportional Fairness Using Iterative-Based Approach" (2020), published in IEEE Access

Li Zhang frequently collaborates with several researchers, including:

  • Chuan Zhang
  • Pingzhi Fan
  • You You
  • Xiaohu You
  • Prabhat Raj Gautam

Best Publications

  • Deep Learning with Differential Privacy

    Martin Abadi;Andy Chu;Ian Goodfellow;H. Brendan McMahan

  • Scalable Influence Maximization in Social Networks under the Linear Threshold Model

    Wei Chen;Yifei Yuan;Li Zhang

  • Learning Differentially Private Recurrent Language Models

    H. Brendan McMahan;Daniel Ramage;Kunal Talwar;Li Zhang

  • Geometric spanners for routing in mobile networks

    Jie Gao;L.J. Guibas;J. Hershberger;Li Zhang

  • TreeJuxtaposer: scalable tree comparison using Focus+Context with guaranteed visibility

    Tamara Munzner;François Guimbretière;Serdar Tasiran;Li Zhang

  • Soft 3D reconstruction for view synthesis

    Eric Penner;Li Zhang

  • Geometric spanner for routing in mobile networks

    Jie Gao;Leonidas J. Guibas;John Hershberger;Li Zhang

  • Tycoon: An implementation of a distributed, market-based resource allocation system

    Kevin Lai;Lars Rasmusson;Eytan Adar;Li Zhang

  • Neural Collaborative Filtering vs. Matrix Factorization Revisited

    Steffen Rendle;Walid Krichene;Li Zhang;John Anderson

  • GLIDER: gradient landmark-based distributed routing for sensor networks

    Qing Fang;Jie Gao;L.J. Guibas;V. de Silva

  • Homomorphic Encryption-Based Privacy-Preserving Federated Learning in IoT-Enabled Healthcare System

    Unknown

  • Analyze gauss: optimal bounds for privacy-preserving principal component analysis

    Cynthia Dwork;Kunal Talwar;Abhradeep Thakurta;Li Zhang

  • Energy clearing price prediction and confidence interval estimation with cascaded neural networks

    Li Zhang;P.B. Luh;K. Kasiviswanathan

  • Discrete mobile centers

    Jie Gao;Leonidas Guibas;John Hershberger;Li Zhang

  • Load-balanced short-path routing in wireless networks

    Jie Gao;Li Zhang

  • Few-Shot Action Recognition with Permutation-Invariant Attention

    Hongguang Zhang;Li Zhang;Xiaojuan Qi;Xiaojuan Qi;Hongdong Li

  • Deformable Free-Space Tilings for Kinetic Collision Detection†:

    Pankaj K. Agarwal;Julien Basch;Leonidas J. Guibas;John Hershberger

  • Learning Polynomials with Neural Networks

    Alexandr Andoni;Rina Panigrahy;Gregory Valiant;Li Zhang

  • The geometry of differential privacy: the sparse and approximate cases

    Aleksandar Nikolov;Kunal Talwar;Li Zhang

  • A price-anticipating resource allocation mechanism for distributed shared clusters

    Michal Feldman;Kevin Lai;Li Zhang

  • Nearly-optimal private LASSO

    Kunal Talwar;Abhradeep Thakurta;Li Zhang

  • Rényi Differential Privacy of the Sampled Gaussian Mechanism.

    Ilya Mironov;Kunal Talwar;Li Zhang

  • Analyze Gauss: optimal bounds for privacy-preserving PCA

    Cynthia Dwork;Kunal Talwar;Abhradeep Thakurta;Li Zhang

Frequent Co-Authors

Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Kunal Talwar
Kunal Talwar Apple (United States)
Jie Gao
Jie Gao Rutgers, The State University of New Jersey
John Hershberger
John Hershberger Mentor Graphics
Rina Panigrahy
Rina Panigrahy Google (United States)
H. Brendan McMahan
H. Brendan McMahan Google (United States)
Kevin Lai
Kevin Lai Samsara
Jeff Erickson
Jeff Erickson University of Illinois at Urbana-Champaign
Daniel Ramage
Daniel Ramage Google (United States)

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