World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
53
Citations
18124
World Ranking
881
National Ranking
423

Engineering and Technology

D-Index
58
Citations
18932
World Ranking
2430
National Ranking
748

Research.com Recognitions

  • 2015 - Member of the National Academy of Engineering For contributions to the theory and application of algorithms for continuous optimization.
  • 2009 - SIAM Fellow For advances in interior point methods and semidefinite programming.
  • 2003 - INFORMS John von Neumann Theory Prize
  • 1988 - Dantzig Prize, by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS)
  • 1981 - Fellow of Alfred P. Sloan Foundation
  • 1980 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

Michael J. Todd is affiliated with Cornell University in the United States. Their research spans multiple fields, prominently mathematics and computer science, with a focus on numerical analysis and computational theory and mathematics.

Their recent publications include:

  • The ellipsoid method redux, 2023, arXiv (Cornell University)
  • An Oblivious Ellipsoid Algorithm for Solving a System of (In)Feasible Linear Inequalities, 2023, Mathematics of Operations Research

Frequent co-authors in their work include:

  • Jourdain Lamperski
  • Robert M. Freund

Michael J. Todd's research covers a variety of topics, including:

  • Advanced Optimization Algorithms Research
  • Polynomial and algebraic computation
  • Complexity and Algorithms in Graphs
  • Iterative Methods for Nonlinear Equations
  • Matrix Theory and Algorithms

Their main fields of study are:

  • Mathematics
  • Computer Science

The subfields of study they contribute to are:

  • Numerical Analysis
  • Computational Theory and Mathematics

Their frequent publication venues are:

  • Mathematics of Operations Research
  • arXiv (Cornell University)

Michael J. Todd has been recognized with several awards throughout their career, including:

  • Member of the National Academy of Engineering (2015) for contributions to the theory and application of algorithms for continuous optimization
  • SIAM Fellow (2009) for advances in interior point methods and semidefinite programming
  • INFORMS John von Neumann Theory Prize (2003)
  • Dantzig Prize by SIAM and the Mathematical Optimization Society (1988)
  • Fellow of Alfred P. Sloan Foundation (1981)
  • Fellow of John Simon Guggenheim Memorial Foundation (1980)

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

  • SDPT3 -- A Matlab Software Package for Semidefinite Programming

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

  • Self-scaled barriers and interior-point methods for convex programming

    Yu E. Nesterov;M. J. Todd

  • Primal-Dual Interior-Point Methods for Self-Scaled Cones

    Yu. E. Nesterov;M. J. Todd

  • The Computation of Fixed Points and Applications

    Michael J. Todd

  • On Adaptive-Step Primal-Dual Interior-Point Algorithms for Linear Programming

    Shinji Mizuno;Michael J. Todd;Yinyu Ye

  • The Ellipsoid Method: A Survey

    Robert G. Bland;Donald Goldfarb;Michael J. Todd

  • An O(nL) -iteration homogeneous and self-dual linear programming algorithm

    Yinyu Ye;Michael J. Todd;Shinji Mizuno

  • Feature Article—The Ellipsoid Method: A Survey

    Robert G. Bland;Donald Goldfarb;Michael J. Todd

  • On the Nesterov--Todd Direction in Semidefinite Programming

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

  • Distance-Weighted Discrimination

    J. S Marron;Michael J Todd;Jeongyoun Ahn

  • The many facets of linear programming

    Michael J. Todd

  • Novel synthetic routes to carbon-nitrogen thin films

    John Kouvetakis;Anil Bandari;Michael Todd;Barry Wilkens

  • Interior-point methods for optimization

    Arkadi S. Nemirovski;Michael J. Todd

  • A centered projective algorithm for linear programming

    Michael J. Todd;Yinyu Ye

  • On Khachiyan's algorithm for the computation of minimum-volume enclosing ellipsoids

    Michael J. Todd;E. Alper Yıldırım

  • Characterization of atrial fibrillation adverse events reported in ibrutinib randomized controlled registration trials

    Jennifer R. Brown;Javid Moslehi;Susan O’Brien;Paolo Ghia

  • An extension of Karmarkar's algorithm for linear programming using dual variables

    Michael J. Todd;Bruce P. Burrell

  • Semidefinite optimization

    Unknown

  • Polynomial Algorithms for Linear Programming

    Michael J. Todd

  • Convex Analysis and Nonlinear Optimization: Theory and Examples. Jonathan M. Borwein and Adrian S. Lewis, Springer, New York, 2000

    Michael J. Todd

Frequent Co-Authors

Marc A. Adams
Marc A. Adams Arizona State University
Howard Tennen
Howard Tennen University of Connecticut
Stephen Armeli
Stephen Armeli Fairleigh Dickinson University
John Kouvetakis
John Kouvetakis Arizona State University
Yinyu Ye
Yinyu Ye Stanford University
Carol B. Cunradi
Carol B. Cunradi Pacific Institute For Research and Evaluation
Kim-Chuan Toh
Kim-Chuan Toh National University of Singapore
Glenn Affleck
Glenn Affleck University of Connecticut Health Center
Barbara E. Ainsworth
Barbara E. Ainsworth Arizona State University
Allan Pinkus
Allan Pinkus Technion – Israel Institute of Technology

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