2026 Jorge Nocedal: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	66	343	287	186	145	156	68583
Engineering and Technology	66	1356	1287	441	395	156	68607

Research.com Recognitions

2020 - Member of the National Academy of Engineering For contributions to the theory, design, and implementation of optimization algorithms and machine learning software.
2017 - INFORMS John von Neumann Theory Prize
2012 - Dantzig Prize, by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS)
2010 - SIAM Fellow For contributions to the theory and practice of continuous optimization.

Overview

Jorge Nocedal is affiliated with Northwestern University in the United States and specializes in research primarily within the fields of Mathematics, Engineering, and Computer Science. Their work prominently addresses areas of Numerical Analysis, Computational Theory and Mathematics, Control and Systems Engineering, Computational Mechanics, and Artificial Intelligence.

The scientist has focused research efforts on a range of topics, including:

Advanced Optimization Algorithms Research
Sparse and Compressive Sensing Techniques
Stochastic Gradient Optimization Techniques
Iterative Methods for Nonlinear Equations
Optimization and Variational Analysis
Model Reduction and Neural Networks
Advanced Multi-Objective Optimization Algorithms

Jorge Nocedal has contributed to numerous research papers published in notable venues. Recent publications include:

"An investigation of Newton-Sketch and subsampled Newton methods," 2020, Optimization methods & software
"Analysis of the BFGS Method with Errors," 2020, SIAM Journal on Optimization
"On the numerical performance of finite-difference-based methods for derivative-free optimization," 2022, Optimization methods & software
"A trust region method for noisy unconstrained optimization," 2023, Mathematical Programming
"Adaptive Finite-Difference Interval Estimation for Noisy Derivative-Free Optimization," 2022, SIAM Journal on Scientific Computing

Frequently, the scientist collaborates with other researchers such as Hao-Jun Michael Shi, Melody Qiming Xuan, Figen Öztoprak, Shigeng Sun, and Yuchen Xie.

The primary publication venues that have featured Jorge Nocedal's work include:

arXiv (Cornell University)
SIAM Journal on Optimization
Optimization methods & software
SIAM Journal on Scientific Computing
Mathematical Programming

Over the course of the career, Jorge Nocedal has been recognized with several awards, such as:

Member of the National Academy of Engineering (2020) for contributions to the theory, design, and implementation of optimization algorithms and machine learning software
INFORMS John von Neumann Theory Prize (2017)
Dantzig Prize by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS) (2012)
SIAM Fellow (2010) for contributions to the theory and practice of continuous optimization

Best Publications

Numerical Optimization

Jorge Nocedal;Stephen J. Wright

15108
Citations
On the limited memory BFGS method for large scale optimization

Dong C. Liu;Jorge Nocedal

9937
Citations
A limited memory algorithm for bound constrained optimization

Richard H. Byrd;Peihuang Lu;Jorge Nocedal;Ciyou Zhu

7452
Citations
Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization

Ciyou Zhu;Richard H. Byrd;Peihuang Lu;Jorge Nocedal

4044
Citations
Updating Quasi-Newton Matrices With Limited Storage

Jorge Nocedal

3648
Citations
Optimization Methods for Large-Scale Machine Learning

Léon Bottou;Frank E. Curtis;Jorge Nocedal

3101
Citations
An Interior Point Algorithm for Large-Scale Nonlinear Programming

Richard H. Byrd;Mary E. Hribar;Jorge Nocedal

2288
Citations
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Nitish Shirish Keskar;Dheevatsa Mudigere;Jorge Nocedal;Mikhail Smelyanskiy

2166
Citations
A trust region method based on interior point techniques for nonlinear programming

Richard H. Byrd;Jean Charles Gilbert;Jorge Nocedal

2115
Citations
Numerical Optimization (Springer Series in Operations Research and Financial Engineering)

Jorge Nocedal;Stephen J. Wright

1766
Citations
Global Convergence Properties of Conjugate Gradient Methods for Optimization

Jean Charles Gilbert;Jorge Nocedal

1547
Citations
Knitro: An Integrated Package for Nonlinear Optimization

Richard H. Byrd;Jorge Nocedal;Richard A. Waltz

1360
Citations
An interior algorithm for nonlinear optimization that combines line search and trust region steps

R. A. Waltz;J. L. Morales;J. Nocedal;D. Orban

1316
Citations
Representations of quasi-Newton matrices and their use in limited memory methods

Richard H. Byrd;Jorge Nocedal;Robert B. Schnabel

1078
Citations
A Stochastic Quasi-Newton Method for Large-Scale Optimization

Richard H. Byrd;S. L. Hansen;Jorge Nocedal;Yoram Singer

568
Citations
A tool for the analysis of Quasi-Newton methods with application to unconstrained minimization

Richard H. Byrd;Jorge Nocedal

547
Citations
Remark on “algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization”

José Luis Morales;Jorge Nocedal

515
Citations
Theory of algorithms for unconstrained optimization

Jorge Nocedal

509
Citations
Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems

Richard H. Byrd;Jorge Nocedal;Ya-Xiang Yuan

499
Citations
Sample size selection in optimization methods for machine learning

Richard H. Byrd;Gillian M. Chin;Jorge Nocedal;Yuchen Wu

431
Citations

Frequent Co-Authors

Richard H. Byrd University of Colorado Boulder

Stephen J. Wright University of Wisconsin–Madison

Nicholas I. M. Gould University of Oxford

Michael L. Overton Courant Institute of Mathematical Sciences

Lorenz T. Biegler Carnegie Mellon University

Ya-xiang Yuan Chinese Academy of Sciences

Mikhail Smelyanskiy Nvidia (United States)

Jong-Shi Pang University of Southern California

Robert B. Schnabel University of Colorado Boulder

Léon Bottou Facebook (United States)

External Links

Wikipedia of Jorge Nocedal Personal website of Jorge Nocedal Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

For students studying Mathematics in the USA, exploring related online degrees can open up diverse career pathways. Many professionals complement their analytical skills with business expertise by pursuing an fastest online mba programs. These programs offer flexibility and accelerated timelines, allowing graduates to quickly advance into leadership roles.

Another popular route is combining math with marketing knowledge, especially through a masters in marketing. This blend enhances data-driven decision-making skills highly valued in today’s job market.

For those focused on business management, choosing among the 1 year mba programs in usa can be a strategic option. These fast-paced degrees balance depth and duration, empowering students to enter the workforce sooner.

Lastly, many students benefit from considering online mba transfer credits, which ease the transition from one degree program to another. This flexibility makes it easier to tailor education to specific career goals.