World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
37
Citations
5919
World Ranking
8361
National Ranking
534

Peter Ross 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 Peter Ross 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: 107 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Peter Ross 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 Peter Ross 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: 37 D-Index — 16th percentile

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

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

Overview

Peter Ross is affiliated with Edinburgh Napier University in the United Kingdom. Their research primarily falls within the field of Medicine, with a focus on several subfields including Oncology, Surgery, Epidemiology, Endocrinology, Diabetes and Metabolism, and Toxicology. The work conducted covers a range of topics related to clinical and surgical oncology, with particular attention to head and neck surgical oncology, pituitary gland disorders and treatments, and management of meningiomas and schwannomas.

The main topics of Peter Ross's research include:

  • Head and Neck Surgical Oncology
  • Pituitary Gland Disorders and Treatments
  • Meningioma and schwannoma management
  • Cancer Immunotherapy and Biomarkers
  • Colorectal Cancer Treatments and Studies
  • Genetic factors in colorectal cancer
  • Pancreatic and Hepatic Oncology Research

Peter Ross is a frequent contributor to a variety of academic journals. The main venues where their work has been published are:

  • Annals of Oncology
  • World Neurosurgery
  • The Journal of Laryngology & Otology
  • British Journal of Neurosurgery
  • Australian Journal of Otolaryngology

Their recent published papers include:

  • CSF Rhinorrhoea After Endonasal Intervention to the Skull Base (CRANIAL) - Part 1: Multicenter Pilot Study, 2021, World Neurosurgery
  • A case series and literature review on patients with rhinological complications secondary to the use of cocaine and levamisole, 2020, The Journal of Laryngology & Otology
  • CSF Rhinorrhea After Endonasal Intervention to the Skull Base (CRANIAL) - Part 2: Impact of COVID-19, 2021, World Neurosurgery
  • CSF rhinorrhoea after endonasal intervention to the anterior skull base (CRANIAL): proposal for a prospective multicentre observational cohort study, 2020, British Journal of Neurosurgery
  • 426P Assessing nivolumab in class II expressing microsatellite stable (pMMR) colorectal cancer (CRC): Results of the ANICCA-Class II trial, 2022, Annals of Oncology

Peter Ross has collaborated regularly with several researchers, including:

  • Danyal Z. Khan
  • Hani J. Marcus
  • Soham Bandyopadhyay
  • Benjamin E. Schroeder
  • Vikesh Patel

Best Publications

  • Hyper-Heuristics: An Emerging Direction in Modern Search Technology

    Edmund K. Burke;Graham Kendall;Jim Newall;Emma Hart

  • A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems

    Hsiao-Lan Fang;Peter Ross;Dave Corne

  • Dynamic Training Subset Selection for Supervised Learning in Genetic Programming

    Chris Gathercole;Peter Ross

  • Adapting operator settings in genetic algorithms

    Andrew Tuson;Peter Ross

  • Credit scoring using neural and evolutionary techniques

    M. B. Yobas;J. N. Crook;P. Ross

  • Some observations about GA-based exam timetabling

    P. Ross;E. Hart;D. Corne

  • Hyper-heuristics: Learning To Combine Simple Heuristics In Bin-packing Problems

    Peter Ross;Sonia Schulenburg;Javier G. Marín-Bläzquez;Emma Hart

  • Fast Practical Evolutionary Timetabling

    David Corne;Peter Ross;Hsiao-Lan Fang

  • Producing robust schedules via an artificial immune system

    E. Hart;P. Ross;J. Nelson

  • Evolutionary Scheduling: A Review

    Emma Hart;Peter Ross;David Corne

  • Evolution of Constraint Satisfaction strategies in examination timetabling

    Hugo Terashima-Marín;Peter Ross;Manuel Valenzuela-Rendón

  • An adverse interaction between crossover and restricted tree depth in genetic programming

    Chris Gathercole;Peter Ross

  • Scheduling, timetabling and rostering — A special relationship?

    Anthony Wren;Edmund K. Burke;Peter Ross

  • A promising hybrid GA/heuristic approach for open-shop scheduling problems

    Hsiao-Lan Fang;Peter Ross;David Corne

  • Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyper-heuristics

    Peter Ross;Javier G. Marín-Blázquez;Sonia Schulenburg;Emma Hart

  • Improving Evolutionary Timetabling with Delta Evaluation and Directed Mutation

    Peter Ross;David Corne;Hsiao-Lan Fang

  • Generalized hyper-heuristics for solving 2D Regular and Irregular Packing Problems

    H. Terashima-Marín;P. Ross;C. J. Farías-Zárate;E. López-Camacho

  • Solving a real-world problem using an evolving heuristically driven schedule builder

    Emma Hart;Peter Ross;Jeremy Nelson

  • GAVEL - a new tool for genetic algorithm visualization

    E. Hart;P. Ross

  • An immune system approach to scheduling in changing environments

    Emma Hart;Peter Ross

Frequent Co-Authors

David Corne
David Corne Heriot-Watt University
Edmund K. Burke
Edmund K. Burke Bangor University
Vaclav Rajlich
Vaclav Rajlich Wayne State University
Gabriela Ochoa
Gabriela Ochoa University of Stirling
Barry Boehm
Barry Boehm University of Southern California
Gerardo Canfora
Gerardo Canfora University of Sannio
Victor R. Basili
Victor R. Basili University of Maryland, College Park
Malcolm Munro
Malcolm Munro Durham University
Dewayne E. Perry
Dewayne E. Perry The University of Texas at Austin

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