World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
39
Citations
6278
World Ranking
2207
National Ranking
930

Engineering and Technology

D-Index
40
Citations
6615
World Ranking
7307
National Ranking
1996

Overview

Shiqian Ma is affiliated with Rice University in the United States and conducts research primarily in the fields of Engineering and Computer Science. Their work spans several subfields including Electrical and Electronic Engineering, Computational Mechanics, Artificial Intelligence, Computational Theory and Mathematics, and Numerical Analysis.

The scientist's research topics emphasize Sparse and Compressive Sensing Techniques, Stochastic Gradient Optimization Techniques, Advanced Optimization Algorithms Research, Microgrid Control and Optimization, Optimal Power Flow Distribution, Optimization and Variational Analysis, and Smart Grid Energy Management.

Shiqian Ma has contributed to numerous academic publications, some of which include:

  • Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold, 2020, SIAM Journal on Optimization
  • An ADMM-based interior-point method for large-scale linear programming, 2020, Optimization methods & software
  • A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization, 2020, Mathematics of Operations Research
  • Active distribution network active and reactive power coordinated dispatching method based on discrete monkey algorithm, 2022, International Journal of Electrical Power & Energy Systems
  • Robust Low-Rank Matrix Completion via an Alternating Manifold Proximal Gradient Continuation Method, 2021, IEEE Transactions on Signal Processing

The venues where this scientist frequently publishes include:

  • arXiv (Cornell University)
  • Mathematics of Operations Research
  • IEEE Transactions on Signal Processing
  • Energies
  • SIAM Journal on Optimization

Shiqian Ma collaborates with several frequent coauthors, among them:

  • Krishnakumar Balasubramanian
  • Shixiang Chen
  • Jiaxiang Li
  • Lingzhou Xue
  • Tianhao Wang

Their research contributions are largely situated in complex optimization problems, algorithm development, and power systems engineering. The blend of practical engineering applications and theoretical algorithmic innovations reflects a multidisciplinary approach to addressing challenges in high-dimensional and large-scale optimization scenarios.

Best Publications

  • Fixed point and Bregman iterative methods for matrix rank minimization

    Shiqian Ma;Donald Goldfarb;Lifeng Chen

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

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

  • Fast alternating linearization methods for minimizing the sum of two convex functions

    Donald Goldfarb;Shiqian Ma;Katya Scheinberg

  • Highly accurate model for prediction of lung nodule malignancy with CT scans.

    Jason L. Causey;Jason L. Causey;Junyu Zhang;Shiqian Ma;Bo Jiang

  • On the Global Linear Convergence of the ADMM with MultiBlock Variables

    Tianyi Lin;Shiqian Ma;Shuzhong Zhang

  • Sparse Inverse Covariance Selection via Alternating Linearization Methods

    Katya Scheinberg;Shiqian Ma;Donald Goldfarb

  • Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization

    Xiao Wang;Shiqian Ma;Donald Goldfarb;Wei Liu

  • Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices

    Lingzhou Xue;Shiqian Ma;Hui Zou

  • Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization

    Caihua Chen;Raymond H. Chan;Shiqian Ma;Junfeng Yang

  • Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization

    Donald Goldfarb;Shiqian Ma

  • Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization

    N. S. Aybat;Z. Wang;T. Lin;S. Ma

  • Barzilai-Borwein step size for stochastic gradient descent

    Conghui Tan;Shiqian Ma;Yu-Hong Dai;Yuqiu Qian

  • Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis

    Bo Jiang;Tianyi Lin;Shiqian Ma;Shuzhong Zhang

  • On the Sublinear Convergence Rate of Multi-block ADMM

    Tian Yi Lin;Shi Qian Ma;Shu Zhong Zhang

  • Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold

    Shixiang Chen;Shiqian Ma;Anthony Man-Cho So;Tong Zhang

  • Alternating direction methods for latent variable gaussian graphical model selection

    Shiqian Ma;Lingzhou Xue;Hui Zou

  • Fast Multiple-Splitting Algorithms for Convex Optimization

    Donald Goldfarb;Shiqian Ma

  • SOLVING MULTIPLE-BLOCK SEPARABLE CONVEX MINIMIZATION PROBLEMS USING TWO-BLOCK ALTERNATING DIRECTION METHOD OF MULTIPLIERS

    Xiangfeng Wang;Mingyi Hong;Shiqian Ma;Zhi-Quan Luo

  • A general inertial proximal point algorithm for mixed variational inequality problem

    Caihua Chen;Shiqian Ma;Junfeng Yang

  • A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization

    Mingyi Hong;Tsung Hui Chang;Xiangfeng Wang;Meisam Razaviyayn

  • ADMM for High-Dimensional Sparse Penalized Quantile Regression

    Yuwen Gu;Jun Fan;Lingchen Kong;Shiqian Ma

  • Positive Definite $ll_1$ Penalized Estimation of Large Covariance Matrices

    Lingzhou Xue;Shiqian Ma;Hui Zou

Frequent Co-Authors

Shuzhong Zhang
Shuzhong Zhang University of Minnesota
Donald Goldfarb
Donald Goldfarb Columbia University
Wei Liu
Wei Liu Tencent (China)
Hui Zou
Hui Zou University of Minnesota
Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign
Anthony Man-Cho So
Anthony Man-Cho So Chinese University of Hong Kong
Lifeng Lai
Lifeng Lai University of California, Davis
Yu-Hong Dai
Yu-Hong Dai Chinese Academy of Sciences
Mingyi Hong
Mingyi Hong University of Minnesota
Zhi-Quan Luo
Zhi-Quan Luo Chinese University of Hong Kong, Shenzhen

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