World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
58
Citations
20707
World Ranking
619
National Ranking
312

Engineering and Technology

D-Index
59
Citations
28529
World Ranking
2273
National Ranking
707

Philip E. Gill publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Philip E. Gill sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 82 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 131 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Philip E. Gill D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Philip E. Gill sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 137 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 58 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2014 - SIAM Fellow For contributions to numerical optimization, linear algebra, and software.

Overview

Philip E. Gill is affiliated with the University of California, San Diego in the United States. Their research spans multiple areas within computer science and mathematics, focusing predominantly on optimization methods and numerical analysis.

The scientist's recent published works include:

  • A Shifted Primal-Dual Penalty-Barrier Method for Nonlinear Optimization, 2020, SIAM Journal on Optimization
  • A Probabilistic Path Planning Framework for Optimizing Feasible Trajectories of Autonomous Search Vehicles Leveraging the Projected-Search Reduced Hessian Method, 2020, AIAA Scitech 2020 Forum
  • A class of projected-search methods for bound-constrained optimization, 2023, Optimization methods & software
  • A projected-search interior-point method for nonlinearly constrained optimization, 2024, Computational Optimization and Applications
  • Projected-Search Methods for Bound-Constrained Optimization, 2021, arXiv (Cornell University)

Their frequent co-authors include Walter Murray, Margaret H. Wright, Minxin Zhang, Michael W. Ferry, and Elizabeth Wong.

Philip E. Gill has published multiple papers in known venues such as:

  • arXiv (Cornell University)
  • SIAM Journal on Optimization
  • Computational Optimization and Applications
  • Optimization methods & software
  • AIAA Scitech 2020 Forum

Their main fields of study are:

  • Computer Science
  • Mathematics

Within these fields, the primary subfields of study are:

  • Computational Theory and Mathematics
  • Numerical Analysis
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Aerospace Engineering

Philip E. Gill's research covers several key topics including:

  • Advanced Optimization Algorithms Research
  • Matrix Theory and Algorithms
  • Numerical Methods and Algorithms
  • Optimization and Variational Analysis
  • Advanced Control Systems Optimization
  • Iterative Methods for Nonlinear Equations
  • Advanced Multi-Objective Optimization Algorithms

In addition, Philip E. Gill has contributed a book titled Numerical Linear Algebra and Optimization, published in 2021 by the Society for Industrial and Applied Mathematics, which has received citations.

They received the SIAM Fellow award in 2014 for contributions to numerical optimization, linear algebra, and software.

Best Publications

  • SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

    Philip E. Gill;Walter Murray;Michael A. Saunders

  • SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

    Philip E. Gill;Walter Murray;Michael A. Saunders

  • Interior Methods for Nonlinear Optimization

    Anders Forsgren;Philip E. Gill;Margaret H. Wright

  • Numerical Linear Algebra and Optimization

    Philip E. Gill;Walter Murray;Margaret H. Wright

  • Algorithms for the Solution of the Nonlinear Least-Squares Problem

    Philip E. Gill;Walter Murray

  • On projected Newton barrier methods for linear programming and an equivalence to Karmarkar's projective method

    Philip E. Gill;Walter Murray;Michael A. Saunders;J. A. Tomlin

  • User's Guide for NPSOL (Version 4.0): A Fortran Package for Nonlinear Programming.

    Philip E Gill;Walter Murray;Michael A Saunders;Margaret H Wright

  • An Augmented Lagrangian Method for Total Variation Video Restoration

    S. H. Chan;R. Khoshabeh;K. B. Gibson;P. E. Gill

  • Newton-type methods for unconstrained and linearly constrained optimization

    Philip E. Gill;Walter Murray

  • Quasi-Newton Methods for Unconstrained Optimization

    P. E. Gill;W. Murray

  • Numerical methods for constrained optimization

    Philip E. Gill;William Allan Murray

  • Aquifer Reclamation Design: The Use of Contaminant Transport Simulation Combined With Nonlinear Programing

    Steven M. Gorelick;Clifford I. Voss;Philip E. Gill;Walter Murray

  • User's Guide for SOL/NPSOL: A Fortran Package for Nonlinear Programming.

    Philip E Gill;Walter Murray;Michael A Saunders;Margaret H Wright

  • Procedures for optimization problems with a mixture of bounds and general linear constraints

    Philip E. Gill;Walter Murray;Michael A. Saunders;Margaret H. Wright

  • USER’S GUIDE FOR SNOPT 5.3: A FORTRAN PACKAGE FOR LARGE-SCALE NONLINEAR PROGRAMMING

    Philip E. Gill;Walter Murray;Michael A. Saunders

  • Numerically stable methods for quadratic programming

    Philip E. Gill;Walter Murray

  • Primal-Dual Interior Methods for Nonconvex Nonlinear Programming

    Anders Forsgren;Philip E. Gill

  • Sequential Quadratic Programming Methods

    Philip E. Gill;Elizabeth Wong

  • Algebraic tensegrity form-finding

    Milenko Masic;Robert E. Skelton;Philip E. Gill

  • Preconditioners for indefinite systems arising in optimization

    Philip E. Gill;Walter Murray;Dulce B. Ponceleón;Michael A. Saunders

  • Methods for modifying matrix factorizations.

    Gene H. Golub;Philip E. Gill;Walter Murray;Michael A. Saunders

Frequent Co-Authors

Walter Murray
Walter Murray Stanford University
Michael A. Saunders
Michael A. Saunders Stanford University
Margaret H. Wright
Margaret H. Wright New York University
Nicholas I. M. Gould
Nicholas I. M. Gould University of Oxford
Truong Q. Nguyen
Truong Q. Nguyen University of California, San Diego
Randolph E. Bank
Randolph E. Bank University of California, San Diego
Linda R. Petzold
Linda R. Petzold University of California, Santa Barbara
Robert E. Skelton
Robert E. Skelton Texas A&M University
Steven Constable
Steven Constable University of California, San Diego
Clifford I. Voss
Clifford I. Voss United States Geological Survey

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

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students interested in expanding their skill set beyond Mathematics, pursuing an online MBA can provide valuable business knowledge paired with analytical expertise. Those looking for quick certification options may consider the shortest online mba degree programs, which allow a faster transition into management roles.

If affordability is a priority, there are several reputable cheapest online masters in finance programs that blend quantitative finance with mathematics principles, opening doors in financial analysis and investment. For advanced executive candidates, dba online programs offer an affordable route to doctoral business administration degrees that emphasize research and leadership.

Additionally, if simplicity and accessibility matter, some students opt for the easiest online mba program options to gain foundational business skills while balancing other commitments. Each of these pathways complements strong mathematical backgrounds, positioning graduates for diverse career opportunities in academia, finance, data science, or corporate leadership.

Best Scientists Citing Philip E. Gill

Trending Scientists

Recently Published Articles