World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
5425
World Ranking
8694
National Ranking
440

Aaron C. Zecchin 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 Aaron C. Zecchin 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: 133 publications — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Aaron C. Zecchin 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 Aaron C. Zecchin 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: 36 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Aaron C. Zecchin is affiliated with the University of Adelaide in Australia. Their research primarily spans the fields of Engineering and Environmental Science, with a particular focus on Civil and Structural Engineering, Ocean Engineering, Global and Planetary Change, Environmental Engineering, and Materials Chemistry.

The scientist contributes extensively to topics related to Water Systems and Optimization, Water Resources Management and Optimization, High Voltage Insulation and Dielectric Phenomena, Geotechnical Engineering and Underground Structures, Flood Risk Assessment and Management, Geophysical Methods and Applications, and Fire Effects on Ecosystems.

Frequent publication venues for Aaron C. Zecchin include:

  • Journal of Water Resources Planning and Management
  • Journal of Hydraulic Engineering
  • SSRN Electronic Journal
  • Water
  • Environmental Modelling & Software

Notable recent papers authored or co-authored by this researcher are:

  • Paired-IRF Method for Detecting Leaks in Pipe Networks (2020), Journal of Water Resources Planning and Management
  • Is renewable energy sustainable? Potential relationships between renewable energy production and the Sustainable Development Goals (2024), npj Climate Action
  • Leak Detection for Pipelines Using In-Pipe Optical Fiber Pressure Sensors and a Paired-IRF Technique (2020), Journal of Hydraulic Engineering
  • Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification (2020), Water Resources Management
  • Elastic Water Column Model for Hydraulic Transient Analysis of Pipe Networks (2022), Journal of Hydraulic Engineering

Aaron C. Zecchin collaborates frequently with several researchers, including:

  • Holger R. Maier
  • Martin F. Lambert
  • Wei Zeng
  • Jinzhe Gong
  • Hedwig van Delden

Best Publications

  • Evolutionary algorithms and other metaheuristics in water resources

    H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat

  • Ant Colony Optimization for Design of Water Distribution Systems

    Holger R. Maier;Angus R. Simpson;Aaron C. Zecchin;Wai Kuan Foong

  • Parametric study for an ant algorithm applied to water distribution system optimization

    A.C. Zecchin;A.R. Simpson;H.R. Maier;J.B. Nixon

  • Application of two ant colony optimisation algorithms to water distribution system optimisation

    Aaron C. Zecchin;Angus R. Simpson;Holger R. Maier;Michael Leonard

  • Ant Colony Optimization Applied to Water Distribution System Design: Comparative Study of Five Algorithms

    Aaron C. Zecchin;Holger R. Maier;Angus R. Simpson;Michael Leonard

  • Battle of the Water Networks II

    Angela Marchi;Elad Salomons;Avi Ostfeld;Zoran Kapelan

  • Hybrid discrete dynamically dimensioned search (HD-DDS) algorithm for water distribution system design optimization.

    Bryan A. Tolson;Masoud Asadzadeh;Holger R. Maier;Aaron Zecchin

  • A combined NLP‐differential evolution algorithm approach for the optimization of looped water distribution systems

    Feifei Zheng;Angus R. Simpson;Aaron C. Zecchin

  • An Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm With Application to Water Distribution System Design Problems

    Feifei Zheng;Aaron C. Zecchin;Jeffery P. Newman;Holger R. Maier

  • Review of literature on decision support systems for natural hazard risk reduction

    Jeffrey Peter Newman;Holger Robert Maier;Graeme Angus Riddell;Aaron Carlo Zecchin

  • Self-Adaptive Differential Evolution Algorithm Applied to Water Distribution System Optimization

    Feifei Zheng;Aaron C. Zecchin;Angus R. Simpson

  • Comparison of the Searching Behavior of NSGA-II, SAMODE, and Borg MOEAs Applied to Water Distribution System Design Problems

    Feifei Zheng;Aaron C. Zecchin;Holger R. Maier;Angus R. Simpson

  • Leak Detection in a Branched System by Inverse Transient Analysis with the Admittance Matrix Method

    Caterina Capponi;Marco Ferrante;Aaron C. Zecchin;Jinzhe Gong

  • ANT COLONY OPTIMIZATION FOR THE DESIGN OF WATER DISTRIBUTION SYSTEMS

    Holger R. Maier;Angus R. Simpson;W. K. Foong;K. Y. Phang

  • Improved PMI-based input variable selection approach for artificial neural network and other data driven environmental and water resource models.

    Xuyuan Li;Holger R. Maier;Aaron C. Zecchin

  • Single-Event Leak Detection in Pipeline Using First Three Resonant Responses

    Jinzhe Gong;Martin F. Lambert;Angus R. Simpson;Aaron C. Zecchin

  • Detection of distributed deterioration in single pipes using transient reflections

    Jinzhe Gong;Angus R. Simpson;Martin F. Lambert;Aaron C. Zecchin

  • Detection of localized deterioration distributed along single pipelines by reconstructive MOC analysis

    Jinzhe Gong;Martin F. Lambert;Angus R. Simpson;Aaron C. Zecchin

  • Selection of smoothing parameter estimators for general regression neural networks - Applications to hydrological and water resources modelling

    Xuyuan Li;Aaron C. Zecchin;Holger R. Maier

  • An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources

    Feifei Zheng;Aaron Zecchin

  • Least squares deconvolution for leak detection with a pseudo random binary sequence excitation

    Si Tran Nguyen Nguyen;Jinzhe Gong;Martin F. Lambert;Aaron C. Zecchin

Frequent Co-Authors

Angus R. Simpson
Angus R. Simpson University of Adelaide
Martin F. Lambert
Martin F. Lambert University of Adelaide
Holger R. Maier
Holger R. Maier University of Adelaide
Graeme C. Dandy
Graeme C. Dandy University of Adelaide
Avi Ostfeld
Avi Ostfeld Technion – Israel Institute of Technology
Patrick M. Reed
Patrick M. Reed Cornell University
Zoran Kapelan
Zoran Kapelan Delft University of Technology
Dragan Savic
Dragan Savic University of Exeter
Barbara S. Minsker
Barbara S. Minsker Southern Methodist University
Andrea Castelletti
Andrea Castelletti Polytechnic University of Milan

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

Engineering and Technology students in the USA can broaden their expertise and career prospects by exploring related online degrees. Specialized programs are now available in areas such as blockchain, UX/UI, project management, and real estate, all of which intersect with modern tech-driven industries.

For those interested in digital finance and security, universities now offer comprehensive blockchain degree programs. These programs provide foundational knowledge in cryptocurrency, fintech, and decentralized systems.

Tech-driven design roles are also in high demand. Enrolling in ux degree programs can help students gain practical skills in user experience and user interface design—a critical need across software and product industries.

If you are drawn towards business or operations management, an online project management degree salary is strong, especially for those managing technical teams or engineering projects.

Finally, engineering graduates interested in property development or construction tech might consider a real estate degree. Online learning allows working professionals to reskill or upskill flexibly, opening doors in both traditional and emerging sectors.

Best Scientists Citing Aaron C. Zecchin

Trending Scientists

Recently Published Articles