World's Best Scientists 2026 revealed!
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Mathematics
Singapore
2026

D-Index & Metrics

Computer Science

D-Index
53
Citations
14811
World Ranking
4728
National Ranking
68

Mathematics

D-Index
53
Citations
14970
World Ranking
888
National Ranking
2

Research.com Recognitions

  • 2026 - Research.com Mathematics in Singapore Leader Award
  • 2025 - Research.com Mathematics in Singapore Leader Award
  • 2022 - Research.com Mathematics in Singapore Leader Award
  • 2018 - SIAM Fellow For his contributions to the development of algorithms and software for semidefinite programming and, more generally, conic programming.

Overview

Kim-Chuan Toh is affiliated with the National University of Singapore and contributes extensively to the fields of computer science, mathematics, and engineering. Their research primarily spans advanced optimization algorithms, sparse and compressive sensing techniques, and optimization and variational analysis. Additional areas of focus include stochastic gradient optimization techniques, statistical methods and inference, matrix theory and algorithms, and numerical methods in inverse problems.

Their work has been published in various well-regarded venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • SIAM Journal on Optimization
  • Mathematical Programming
  • Mathematics of Operations Research
  • Mathematical Programming Computation

Notable papers authored under their guidance or collaboration include:

  • "An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming" (2020, SIAM Journal on Optimization)
  • "Difference-of-Convex Algorithms for a Class of Sparse Group ℓ0 Regularized Optimization Problems" (2022, SIAM Journal on Optimization)
  • "An inexact projected gradient method with rounding and lifting by nonlinear programming for solving rank-one semidefinite relaxation of polynomial optimization" (2022, Mathematical Programming)
  • "Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian" (2020, SIAM Journal on Optimization)
  • "Bregman Proximal Point Algorithm Revisited: A New Inexact Version and Its Inertial Variant" (2022, SIAM Journal on Optimization)

The scientist has collaborated frequently with a core group of researchers. The most common coauthors include:

  • Defeng Sun
  • Ling Liang
  • Nachuan Xiao
  • Xiaoyin Hu
  • Tianyun Tang

Kim-Chuan Toh's specific subfields of study reflect an emphasis on computational and theoretical aspects:

  • Numerical Analysis
  • Computational Theory and Mathematics
  • Computational Mechanics
  • Artificial Intelligence
  • Statistics and Probability

Recognition within the scientific community includes earning the distinction of SIAM Fellow in 2018 for contributions to algorithms and software development targeting semidefinite programming and broader conic programming.

Best Publications

  • SDPT3 — A Matlab software package for semidefinite programming, Version 1.3

    K. C. Toh;M. J. Todd;R. H. Tütüncü

  • Solving semidefinite-quadratic-linear programs using SDPT3

    Reha H. Tütüncü;Kim-Chuan Toh;Michael J. Todd

  • An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems

    Kim-Chuan Toh;Sangwoon Yun

  • SDPT3 -- A Matlab Software Package for Semidefinite Programming

    K. C. Toh;M. J. Todd;R. H. Tutuncu

  • Semidefinite Programming Approaches for Sensor Network Localization With Noisy Distance Measurements

    P. Biswas;Tzu-Chen Liang;Kim-Chuan Toh;Y. Ye

  • A Newton-CG Augmented Lagrangian Method for Semidefinite Programming

    Xin-Yuan Zhao;Defeng Sun;Kim-Chuan Toh

  • On the Nesterov--Todd Direction in Semidefinite Programming

    M. J. Todd;K. C. Toh;R. H. Tütüncü

  • SDPNAL$$$$: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints

    Liuqin Yang;Defeng Sun;Kim-Chuan Toh

  • On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0

    Kim-Chuan Toh;Michael J. Todd;Reha H. Tütüncü

  • SDPT3 — a Matlab software package for semidefinite-quadratic-linear programming, version 3.0

    R. H. Tütüncü;K. C. Toh;M. J. Todd

  • A Convergent 3-Block SemiProximal Alternating Direction Method of Multipliers for Conic Programming with 4-Type Constraints

    Defeng Sun;Kim-Chuan Toh;Liuqin Yang

  • An inexact interior point method for L1-regularized sparse covariance selection

    Lu Li;Kim-Chuan Toh;Kim-Chuan Toh

  • A highly efficient semismooth Newton augmented lagrangian method for solving lasso problems

    Xudong Li;Defeng Sun;Defeng Sun;Kim Chuan Toh

  • A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions

    Xudong Li;Defeng Sun;Kim-Chuan Toh

  • An efficient inexact symmetric Gauss---Seidel based majorized ADMM for high-dimensional convex composite conic programming

    Liang Chen;Defeng Sun;Kim-Chuan Toh

  • 3D Chromosome Modeling with Semi-Definite Programming and Hi-C Data

    ZhiZhuo Zhang;Guoliang Li;Kim-Chuan Toh;Wing-Kin Sung

  • A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation

    Pratik Biswas;Kim-Chuan Toh;Yinyu Ye

  • From Potential Theory to Matrix Iterations in Six Steps

    Tobin A. Driscoll;Kim-Chuan Toh;Lloyd N. Trefethen

  • An implementable proximal point algorithmic framework for nuclear norm minimization

    Yong-Jin Liu;Defeng Sun;Kim-Chuan Toh

  • Pseudozeros of Polynomials and Pseudospectra of Companion Matrices

    Kim-Chuan Toh;Lloyd N. Trefethen

  • A Convergent 3-Block Semi-Proximal Alternating Direction Method of Multipliers for Conic Programming with $4$-Type of Constraints

    Defeng Sun;Kim-Chuan Toh;Liuqin Yang

Frequent Co-Authors

Defeng Sun
Defeng Sun Hong Kong Polytechnic University
Kok-Kwang Phoon
Kok-Kwang Phoon Singapore University of Technology and Design
Masakazu Kojima
Masakazu Kojima Tokyo Institute of Technology
Michael J. Todd
Michael J. Todd Cornell University
Lloyd N. Trefethen
Lloyd N. Trefethen University of Oxford
Jean B. Lasserre
Jean B. Lasserre Laboratory for Analysis and Architecture of Systems
Zuowei Shen
Zuowei Shen National University of Singapore
Stephen A. Vavasis
Stephen A. Vavasis University of Waterloo
Fook Hou Lee
Fook Hou Lee National University of Singapore
Wing-Kin Sung
Wing-Kin Sung Chinese University of Hong Kong

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