World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
39
Citations
8134
World Ranking
7568
National Ranking
2077

Kash Barker publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Kash Barker sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 153 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Kash Barker D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Kash Barker sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 39 D-Index — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Kash Barker is affiliated with the University of Oklahoma in the United States. Their research primarily spans the field of engineering, with a significant focus on civil and structural engineering as well as intersections with sociology, political science, computer networks, statistical physics, and control systems engineering.

The main topics in Barker's work include infrastructure resilience and vulnerability analysis, complex network analysis techniques, smart grid security and resilience, facility location and emergency management, network security and intrusion detection, risk and safety analysis, and disaster management and resilience.

Among their recent publications are:

  • "Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience," 2020, Reliability Engineering & System Safety
  • "Social vulnerability and equity perspectives on interdependent infrastructure network component importance," 2020, Sustainable Cities and Society
  • "Exploring Recovery Strategies for Optimal Interdependent Infrastructure Network Resilience," 2021, Networks and Spatial Economics
  • "A decomposition approach for solving tri-level defender-attacker-defender problems," 2021, Computers & Industrial Engineering
  • "Multi-objective reliability redundancy allocation using MOPSO under hesitant fuzziness," 2022, Expert Systems with Applications

Barker frequently publishes in several venues, including:

  • Reliability Engineering & System Safety
  • Risk Analysis
  • Computers & Industrial Engineering
  • Environment Systems & Decisions
  • Socio-Economic Planning Sciences

They have collaborated extensively with several coauthors, such as:

  • Andrés D. González (32 publications)
  • Sridhar Radhakrishnan (14 publications)
  • Claudio M. Rocco (11 publications)
  • Nafiseh Ghorbani-Renani (8 publications)
  • Buket Cilali (6 publications)

Best Publications

  • A review of definitions and measures of system resilience

    Seyedmohsen Hosseini;Kash Barker;Jose Emmanuel Ramirez-Marquez;Jose Emmanuel Ramirez-Marquez

  • Resilience-based network component importance measures

    Kash Barker;Jose Emmanuel Ramirez-Marquez;Claudio M. Rocco

  • Modeling infrastructure resilience using Bayesian networks

    Seyedmohsen Hosseini;Kash Barker

  • Resilient supplier selection and optimal order allocation under disruption risks

    Seyedmohsen Hosseini;Nazanin Morshedlou;Dmitry Ivanov;M.D. Sarder

  • A Bayesian network model for resilience-based supplier selection

    Seyedmohsen Hosseini;Kash Barker

  • Stochastic measures of resilience and their application to container terminals

    Raghav Pant;Kash Barker;Jose Emmanuel Ramirez-Marquez;Claudio M. Rocco

  • Resilience-driven restoration model for interdependent infrastructure networks

    Yasser Almoghathawi;Yasser Almoghathawi;Kash Barker;Laura A. Albert

  • Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors

    Raghav Pant;Kash Barker;Christopher W. Zobel

  • Importance measures for inland waterway network resilience

    Hiba Baroud;Kash Barker;Jose E. Ramirez-Marquez;M S Claudio Rocco

  • Measuring the efficacy of inventory with a dynamic input–output model

    Kash Barker;Joost R. Santos

  • Measuring changes in international production from a disruption: Case study of the Japanese earthquake and tsunami

    Cameron A. MacKenzie;Joost R. Santos;Kash Barker

  • Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

    Hiba Baroud;Jose E. Ramirez-Marquez;Kash Barker;Claudio M. Rocco

  • Multidimensional approach to complex system resilience analysis

    Dante Gama Dessavre;Jose Emmanuel Ramirez-Marquez;Jose Emmanuel Ramirez-Marquez;Kash Barker

  • Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning

    Charles D. Nicholson;Kash Barker;Jose Emmanuel Ramirez-Marquez;Jose Emmanuel Ramirez-Marquez

  • Interdependent impacts of inoperability at multi-modal transportation container terminals

    Raghav Pant;Kash Barker;F. Hank Grant;Thomas L. Landers

  • Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors

    Kash Barker;Yacov Y. Haimes

  • Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience

    Nafiseh Ghorbani-Renani;Andrés D. González;Kash Barker;Nazanin Morshedlou

  • Modeling a severe supply chain disruption and post-disaster decision making with application to the Japanese earthquake and tsunami

    Cameron A. MacKenzie;Kash Barker;Joost R. Santos

  • Inherent Costs and Interdependent Impacts of Infrastructure Network Resilience

    Hiba Baroud;Kash Barker;Jose E. Ramirez-Marquez;Claudio M. Rocco

  • Defining resilience analytics for interdependent cyber-physical-social networks

    Kash Barker;James H. Lambert;Christopher W. Zobel;Andrea H. Tapia

  • Evaluating the Consequences of an Inland Waterway Port Closure With a Dynamic Multiregional Interdependence Model

    C. A. MacKenzie;K. Barker;F. H. Grant

  • Community resilience-driven restoration model for interdependent infrastructure networks

    Deniz Berfin Karakoc;Yasser Almoghathawi;Kash Barker;Andrés D. González

Frequent Co-Authors

Jose Emmanuel Ramirez-Marquez
Jose Emmanuel Ramirez-Marquez Stevens Institute of Technology
Yacov Y. Haimes
Yacov Y. Haimes University of Virginia
James H. Lambert
James H. Lambert University of Virginia
Dmitry Ivanov
Dmitry Ivanov Berlin School of Economics and Law
Cornelia Caragea
Cornelia Caragea University of Illinois at Chicago

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