World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
16998
World Ranking
6023
National Ranking
797

Mathematics

D-Index
46
Citations
16382
World Ranking
1315
National Ranking
70

Overview

Yin Zhang is affiliated with the Chinese University of Hong Kong, Shenzhen in China. Their research spans multiple disciplines, primarily focusing on computer science and physics and astronomy. Within these broad fields, their work delves into several subfields including artificial intelligence, atomic and molecular physics and optics, computational theory and mathematics, statistical and nonlinear physics, and condensed matter physics.

Their study topics prominently cover quantum computing algorithms and architecture, quantum information and cryptography, and quantum many-body systems, with additional work related to quantum and electron transport phenomena, physics of superconductivity and magnetism, surface and thin film phenomena, and materials such as Ga2O3.

Recent publications demonstrate a focus on both theoretical and applied aspects of quantum science and materials physics. Notable papers include:

  • Eliminating Surface Oxides of Superconducting Circuits with Noble Metal Encapsulation, 2025, Physical Review Letters
  • Tight-binding band structure of β- and α-phase Ga2O3 and Al2O3, 2022, Journal of Applied Physics
  • Characterizing Matrix-Product States and Projected Entangled-Pair States Preparable via Measurement and Feedback, 2024, PRX Quantum
  • Nonlocal growth of quantum conditional mutual information under decoherence, 2024, Physical review. A/Physical review, A
  • Classical Simulability of Quantum Circuits with Shallow Magic Depth, 2025, PRX Quantum

Yin Zhang has published extensively in several venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Physical Review Letters
  • PRX Quantum
  • Journal of Applied Physics
  • Physical review. A/Physical review, A

Their research collaborations include work with several co-authors, notably:

  • Sarang Gopalakrishnan
  • Ray Chang
  • Nana Shumiya
  • Russell A. McLellan
  • Matthew Bland

Best Publications

  • A New Alternating Minimization Algorithm for Total Variation Image Reconstruction

    Yilun Wang;Junfeng Yang;Wotao Yin;Yin Zhang

  • Alternating Direction Algorithms for $ll_1$-Problems in Compressive Sensing

    Junfeng Yang;Yin Zhang

  • Fixed-Point Continuation for $ll_1$-Minimization: Methodology and Convergence

    Elaine T. Hale;Wotao Yin;Yin Zhang

  • Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm

    Zaiwen Wen;Wotao Yin;Yin Zhang

  • An efficient augmented Lagrangian method with applications to total variation minimization

    Chengbo Li;Wotao Yin;Hong Jiang;Yin Zhang

  • A Fast Alternating Direction Method for TVL1-L2 Signal Reconstruction From Partial Fourier Data

    Junfeng Yang;Yin Zhang;Wotao Yin

  • A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration

    Junfeng Yang;Wotao Yin;Yin Zhang;Yilun Wang

  • On the formulation and theory of the Newton interior-point method for nonlinear programming

    A. S. El-Bakry;A. S. El-Bakry;R. A. Tapia;T. Tsuchiya;Y. Zhang;Y. Zhang

  • Solving large-scale linear programs by interior-point methods under the Matlab ∗ Environment †

    Yin Zhang

  • An efficient algorithm for compressed MR imaging using total variation and wavelets

    Shiqian Ma;Wotao Yin;Yin Zhang;A. Chakraborty

  • An Efficient TVL1 Algorithm for Deblurring Multichannel Images Corrupted by Impulsive Noise

    Junfeng Yang;Yin Zhang;Wotao Yin

  • On Extending Some Primal--Dual Interior-Point Algorithms From Linear Programming to Semidefinite Programming

    Yin Zhang

  • An alternating direction algorithm for matrix completion with nonnegative factors

    Yangyang Xu;Wotao Yin;Zaiwen Wen;Yin Zhang

  • On the Convergence of a Class of Infeasible Interior-Point Methods for the Horizontal Linear Complementarity Problem

    Yin Zhang

  • Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization

    Y. Shen;Z. Wen;Y. Zhang

  • Group Sparse Optimization by Alternating Direction Method

    Wei Deng;Wotao Yin;Yin Zhang

  • Dynamic ventilation imaging from four-dimensional computed tomography.

    Thomas Guerrero;Thomas Guerrero;Kevin Sanders;Edward Castillo;Yin Zhang

  • A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation

    Zaiwen Wen;Wotao Yin;Donald Goldfarb;Yin Zhang

  • Rank-Two Relaxation Heuristics for MAX-CUT and Other Binary Quadratic Programs

    Samuel Burer;Renato D. C. Monteiro;Yin Zhang

  • A Compressive Sensing and Unmixing Scheme for Hyperspectral Data Processing

    Chengbo Li;Ting Sun;K. F. Kelly;Yin Zhang

Frequent Co-Authors

Wotao Yin
Wotao Yin Alibaba Group (China)
Renato D. C. Monteiro
Renato D. C. Monteiro Georgia Institute of Technology
George N. Phillips
George N. Phillips Rice University
Samuel Burer
Samuel Burer University of Iowa
Yinyu Ye
Yinyu Ye Stanford University
Stephen J. Wright
Stephen J. Wright University of Wisconsin–Madison
Ritsuko Komaki
Ritsuko Komaki The University of Texas MD Anderson Cancer Center
Richard H. Byrd
Richard H. Byrd University of Colorado Boulder
Donald Goldfarb
Donald Goldfarb Columbia University
Jay D. Keasling
Jay D. Keasling University of California, Berkeley

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