2026 James V. Burke: Mathematics Researcher – H-Index, Publications & Awards

D-Index & Metrics

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	49	1166	997	523	413	126	7403
Engineering and Technology	49	4413	4245	1264	1164	126	7396

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

1166

997

523

413

126

7403

Engineering and Technology

4413

4245

1264

1164

126

7396

Mathematics

D-Index

Citations

7403

World Ranking

1166

National Ranking

523

Engineering and Technology

D-Index

Citations

7396

World Ranking

4413

National Ranking

1264

Research.com Recognitions

1983 - SPIE Fellow

Overview

James V. Burke is affiliated with the University of Washington in the United States. Their research spans multiple fields, with a primary focus on mathematics and computer science. The subfields of their work include statistics and probability, computational mechanics, computational theory and mathematics, numerical analysis, and artificial intelligence.

Burke's research covers several main topics, including:

Sparse and Compressive Sensing Techniques
Optimization and Variational Analysis
Advanced Optimization Algorithms Research
Advanced Causal Inference Techniques
Mental Health Research Topics
Numerical Methods in Inverse Problems
Bayesian Methods and Mixture Models

Their recent publications reflect their work's focus on optimization, algorithms, and statistical methods. Notable papers include:

"An Algorithm for Nonparametric Estimation of a Multivariate Mixing Distribution with Applications to Population Pharmacokinetics," 2020, Pharmaceutics
"Strong Metric (Sub)regularity of Karush-Kuhn-Tucker Mappings for Piecewise Linear-Quadratic Convex-Composite Optimization and the Quadratic Convergence of Newton's Method," 2020, Mathematics of Operations Research
"Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver," 2020, SIAM Journal on Optimization
"Convergence of the Gradient Sampling Algorithm on Directionally Lipschitz Functions," 2021, Set-Valued and Variational Analysis
"A Relaxation Approach to Feature Selection for Linear Mixed Effects Models," 2023, Journal of Computational and Graphical Statistics

Frequent publication venues for Burke include:

Mathematics of Operations Research
arXiv (Cornell University)
Pharmaceutics
SIAM Journal on Optimization
Journal of Computational and Graphical Statistics

The scientist has collaborated with several researchers, with repeated coauthors such as:

Aleksandr Y. Aravkin
Aleksei Sholokhov
Damian Santomauro
Walter M. Yamada
Michael Neely

James V. Burke was awarded the distinction of SPIE Fellow in 1983, marking an acknowledgment within the scientific community.

Best Publications

A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization

James V. Burke;Adrian S. Lewis;Michael L. Overton

557
Citations
Weak sharp minima in mathematical programming

J. V. Burke;M. C. Ferris

447
Citations
HIFOO - A MATLAB package for fixed-order controller design and H ∞ optimization

J.V. Burke;D. Henrion;A.S. Lewis;M.L. Overton

343
Citations
An exact penalization viewpoint of constrained optimization

James V. Burke

308
Citations
On the identification of active constraints

James V. Burke;Jorge J. Moré

278
Citations
Optical Wavefront Reconstruction: Theory and Numerical Methods

D. Russell Luke;James V. Burke;Richard G. Lyon

225
Citations
On the Lidskii--Vishik--Lyusternik Perturbation Theory for Eigenvalues of Matrices with Arbitrary Jordan Structure

Julio Moro;James V. Burke;Michael L. Overton

208
Citations
Stabilization via Nonsmooth, Nonconvex Optimization

J.V. Burke;D. Henrion;A.S. Lewis;M.L. Overton

197
Citations
Calmness and exact penalization

J. V. Burke

186
Citations
A robust sequential quadratic programming method

J. V. Burke;S.-P. Han

183
Citations
The Global Linear Convergence of a Noninterior Path-Following Algorithm for Linear Complementarity Problems

James V. Burke;Song Xu

174
Citations
A Gauss-Newton method for convex composite optimization

J. V. Burke;M. C. Ferris

167
Citations
Descent methods for composite nondifferentiable optimization problems

James V. Burke

148
Citations
Approximating Subdifferentials by Random Sampling of Gradients

J. V. Burke;A. S. Lewis;M. L. Overton

138
Citations
Weak sharp minima revisited Part I: basic theory

James V. Burke

137
Citations
Characterization of solution sets of convex programs

J. V. Burke;M. C. Ferris

131
Citations
A non–interior predictor–corrector path following algorithm for the monotone linear complementarity problem

James V. Burke;Song Xu

130
Citations
Generalized Kalman smoothing: Modeling and algorithms

Aleksandr Y. Aravkin;James V. Burke;Lennart Ljung;Aurelie C. Lozano

125
Citations
Convergence properties of trust region methods for linear and convex constraints

J. V. Burke;J. J. Moré;G. Toraldo

118
Citations
Two numerical methods for optimizing matrix stability

James V. Burke;Adrian S. Lewis;Michael L. Overton

113
Citations
Weak sharp minima revisited, part II: application to linear regularity and error bounds

James V. Burke;Sien Deng

111
Citations

Frequent Co-Authors

Gianluigi Pillonetto University of Padua

Michael L. Overton Courant Institute of Mathematical Sciences

Adrian S. Lewis Cornell University

Alessandro Chiuso University of Padua

Michael C. Ferris University of Wisconsin–Madison

Paul Tseng University of Washington

Jorge J. Moré Argonne National Laboratory

Jonathan M. Borwein University of Newcastle Australia

Lennart Ljung Linköping University

Yinyu Ye Stanford University

External Links

Personal website of James V. Burke Google Scholar page

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