World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
44
Citations
8038
World Ranking
1587
National Ranking
685

George C. Runger 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 George C. Runger 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: 83 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: 110 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

George C. Runger 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 George C. Runger 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: 138 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: 44 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

George C. Runger is affiliated with Arizona State University in the United States. Their research primarily focuses on various domains within computer science, with a particular emphasis on artificial intelligence and its applications.

The scientist's main fields of study include:

  • Computer Science

Within this broad area, their subfields of study cover:

  • Artificial Intelligence
  • General Health Professions
  • Industrial and Manufacturing Engineering
  • Food Science
  • Molecular Biology

Their work addresses multiple topics, notably:

  • Machine Learning and Algorithms
  • Scheduling and Optimization Algorithms
  • Gaussian Processes and Bayesian Inference
  • Food Supply Chain Traceability
  • Food Waste Reduction and Sustainability
  • Health disparities and outcomes
  • Food Security and Health in Diverse Populations

George C. Runger has published research in various scientific venues, including:

  • Test
  • arXiv (Cornell University)
  • BMC Bioinformatics
  • SSRN Electronic Journal
  • Journal of Cleaner Production

Recent papers authored by or involving George C. Runger include:

  • "Dynamic incorporation of prior knowledge from multiple domains in biomarker discovery," 2020, BMC Bioinformatics
  • "Attention-Based Reinforcement Learning for Combinatorial Opti Mization: Application to Job Shop Scheduling Problem," 2024, SSRN Electronic Journal
  • "On active learning methods for manifold data," 2020, Test
  • "Building an intelligent system to identify trends in agricultural markets," 2023, Journal of Cleaner Production
  • "Layered Market Intelligence System," 2022, Transportation Research Procedia

The scientist frequently collaborates with a group of co-authors that includes:

  • Li Liu
  • Kailey Love
  • Seho Kee
  • Mani Janakiram
  • Enrique Del Castillo

Best Publications

  • Comparisons of Multivariate CUSUM Charts

    Joseph J. Pignatiello;George C. Runger

  • A Combined Adaptive Sample Size and Sampling Interval X Control Scheme

    Sharad S. Prabhu;Douglas C. Montgomery;George C. Runger

  • Using Experimental Design to Find Effective Parameter Settings for Heuristics

    Steven P. Coy;Bruce L. Golden;George C. Runger;Edward A. Wasil

  • GAUGE CAPABILITY AND DESIGNED EXPERIMENTS. PART I: BASIC METHODS

    Douglas C. Montgomery;George C. Runger

  • Adaptive Sampling for Process Control

    George C. Runger;Joseph J. Pignatiello

  • A Markov Chain Model for the Multivariate Exponentially Weighted Moving Averages Control Chart

    George C. Runger;Sharad S. Prabhu

  • X¯ chart with adaptive sample sizes

    Unknown

  • Applied Statistics and Probability for Engineers sixth edition

    Douglas C. Montgomery;George C. Runger

  • Optimization Problems and Methods in Quality Control and Improvement

    W. Matthew Carlyle;Douglas C. Montgomery;George C. Runger

  • The Analysis of Transformed Data

    Unknown

  • Bias of importance measures for multi-valued attributes and solutions

    Houtao Deng;George Runger;Eugene Tuv

  • ADAPTIVE SAMPLING ENHANCEMENTS FOR SHEWHART CONTROL CHARTS

    George C. Runger;Douglas C. Montgomery

  • GAUGE CAPABILITY ANALYSIS AND DESIGNED EXPERIMENTS. PART II: EXPERIMENTAL DESIGN MODELS AND VARIANCE COMPONENT ESTIMATION

    Douglas C. Montgomery;George C. Runger

  • Process monitoring for multiple count data using generalized linear model-based control charts

    Katina R. Skinner;Douglas C. Montgomery;George C. Runger

  • Contributors to a multivariate statistical process control chart signal

    George C. Runger;Frank B. Alt;Douglas C. Montgomery

  • Model-Based and Model-Free Control of Autocorrelated Processes

    Unknown

  • Guidelines for the application of adaptive control charting schemes

    Lora S. Zimmer;Douglas C. Montgomery;George C. Runger

  • Multivariate statistical process monitoring and diagnosis with grouped regression‐adjusted variables

    Daryl J. Hauck;George C. Runger;Douglas C. Montgomery

  • Designing control charts using an empirical reference distribution

    Unknown

  • Foldovers of 2k-p Resolution IV Experimental Designs

    Douglas C. Montgomery;George C. Runger

  • A review of statistical process control techniques for short run manufacturing systems

    Enrique Del Castillo;James M. Grayson;Douglas C. Montgomery;George C. Runger

  • Optimal monitoring of multivariate data for fault patterns

    George C. Runger;Russell Richard Barton;Enrique Del Castillo;William H. Woodall

  • See the forest before the trees: fine-tuned learning and its application to the traveling salesman problem

    S.P. Coy;B.L. Golden;G.C. Runger;E.A. Wasil

  • Applied Statistics and Probability for Engineers, Student Solutions Manual

    Douglas C. Montgomery;George C. Runger

  • Adaptive controllers to integrate SPC and EPC

    Yuehjen E. Shao;George C. Runger;Jorge Haddock;W. A. Wallace

  • Neural network models for initial public offerings

    Steven J. Robertson;Bruce L. Golden;George C. Runger;Edward A. Wasil

  • Statistical process control using level crossings

    Thomas R. Willemain;George C. Runger

  • Statistical process control using run sums

    Thomas R. Willemain;George C. Runger

  • On active learning methods for manifold data

    Hang Li;Enrique Del Castillo;George Runger

  • Optimal multivariate bounded adjustment

    George Runger;Zilong Lian;Enrique Del Castillo

  • Probability and Statistics for Engineers

    George C. Runger;Douglas C. Montgomery

  • An introduction to a new journal for Healthcare Systems Engineering

    John W. Fowler;James C. Benneyan;Pascale Carayon;Brian T. Denton

  • Most powerful invariant permutation tests

    George C. Runger;M. L. Eaton

Frequent Co-Authors

Douglas C. Montgomery
Douglas C. Montgomery Arizona State University

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Related Online Degrees & Career Pathways

For students pursuing Mathematics in the USA, exploring related online degrees can open up diverse career opportunities. Many professionals complement their math background with a Master in Data Analytics, a field that applies mathematical principles to interpret complex data sets, driving decision-making in various industries. This degree is increasingly offered online, allowing for flexible learning focused on practical skills.

For those interested in leadership roles or expanding their business acumen, year long MBA programs offer an accelerated pathway. These programs are designed to build managerial expertise quickly, ideal for math graduates aiming to combine technical and business skills.

Additionally, many students wonder if they can transfer credits between programs to save time and costs. The answer is yes, with numerous can you transfer MBA programs options available online, making academic progression more flexible and personalized.

Students concerned about admissions can also consider MBA programs easy to get into, which provide accessible entry points without compromising the quality of education. Combining these pathways with a strong math foundation greatly enhances career prospects across sectors like finance, technology, and analytics.

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