World's Best Scientists 2026 revealed!
David G. Luenberger

David G. Luenberger

D-Index & Metrics

Engineering and Technology

D-Index
32
Citations
23876
World Ranking
9495
National Ranking
2672

Research.com Recognitions

  • 2008 - Member of the National Academy of Engineering For contributions to control theory, optimization algorithms, and economic dynamics.
  • 1998 - Rufus Oldenburger Medal, The American Society of Mechanical Engineers

Overview

David G. Luenberger is affiliated with Stanford University in the United States. Their academic work spans multiple fields including Mathematics, Computer Science, and Engineering, with a particular focus on Numerical Analysis, Computational Theory and Mathematics, Computational Mechanics, Management Science and Operations Research, and Control and Systems Engineering.

The scientist's research covers a range of main topics, which include:

  • Advanced Optimization Algorithms Research
  • Optimization and Variational Analysis
  • Sparse and Compressive Sensing Techniques
  • Advanced Multi-Objective Optimization Algorithms
  • Matrix Theory and Algorithms
  • Iterative Methods for Nonlinear Equations
  • Stochastic Gradient Optimization Techniques

Luenberger has collaborated frequently with co-author Yinyu Ye, contributing to multiple works together. Their influence extends into publishing, with a notable book published by Springer Science+Business Media titled Linear and Nonlinear Programming, released in 2021 and cited extensively.

The researcher's work has been recognized through awards such as the Rufus Oldenburger Medal from The American Society of Mechanical Engineers in 1998. Additionally, they became a Member of the National Academy of Engineering in 2008 for their contributions to control theory, optimization algorithms, and economic dynamics.

Best Publications

  • Optimization by Vector Space Methods

    David G. Luenberger

  • An introduction to observers

    D. Luenberger

  • Observers for multivariable systems

    D. Luenberger

  • Observing the State of a Linear System

    David G. Luenberger

  • Dynamic equations in descriptor form

    D. Luenberger

  • Canonical forms for linear multivariable systems

    D. Luenberger

  • Estimation of structured covariance matrices

    J.P. Burg;D.G. Luenberger;D.L. Wenger

  • State space analysis of control systems

    D. Luenberger

  • Paper: Time-invariant descriptor systems

    David G. Luenberger

  • New optimality principles for economic efficiency and equilibrium

    D. G. Luenberger

  • Approximation of linear constant systems

    L. Meier;D. Luenberger

  • The Gradient Projection Method Along Geodesics

    Unknown

  • Self-Scaling Variable Metric (SSVM) Algorithms

    Shmuel S. Oren

  • Quasi-Convex Programming

    Unknown

  • Design of multivariable feedback systems

    B.D.O. Anderson;D.G. Luenberger

  • Non-linear descriptor systems

    David G. Luenberger

  • Differential games with imperfect state information

    Unknown

  • The Conjugate Residual Method for Constrained Minimization Problems

    David G. Luenberger

  • Control problems with kinks

    D. Luenberger

  • Stochastic differential games with constrained state estimators

    I. Rhodes;D. Luenberger

  • A preference foundation for log mean-variance criteria in portfolio choice problems

    David G. Luenberger

  • Decomposition of Real and Reactive Power Flows: A Method Suited for On-Line Applications

    Charles H. Jolissaint;N. V. Arvanitidis;David G. Luenberger

  • Analysis of the Asymptotic Behavior of Optimal Control Trajectories: The Implicit Programming Problem

    C. D. Feinstein;D. G. Luenberger

Frequent Co-Authors

Yinyu Ye
Yinyu Ye Stanford University
Daniel Kuhn
Daniel Kuhn École Polytechnique Fédérale de Lausanne

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