World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
4551
World Ranking
8781
National Ranking
2438

Angelo Miele 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 Angelo Miele 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: 191 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Angelo Miele 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 Angelo Miele 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

Angelo Miele was affiliated with Rice University in the United States and contributed to research primarily in the fields of Computer Vision and Pattern Recognition as well as Computer Networks and Communications. Their work focused on topics including Robotic Path Planning Algorithms and Distributed Control in Multi-Agent Systems.

The scientist published multiple papers in peer-reviewed venues, reflecting a concentration on distributed coordination and networked multi-agent systems. Notable publications include:

  • "A Distributed Framework for Integrated Task Allocation and Safe Coordination in Networked Multi-Robot Systems" (2025, IEEE Transactions on Automation Science and Engineering)
  • "Gossip-Based Estimation of Centroid and Common Reference Frame in Open Multi-Agent Systems" (2025, IEEE Control Systems Letters)
  • "Discrete-Time Distributed Potential-Based Coordination in Networked Multi-Agent Systems" (2025, IEEE Control Systems Letters)
  • "No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO" (2024, arXiv (Cornell University))

The venues where the scientist frequently published include:

  • IEEE Control Systems Letters
  • IEEE Transactions on Automation Science and Engineering
  • arXiv (Cornell University)

Collaborations formed an important part of the scientist's academic work, with several frequent co-authors contributing to their research. These included Andrea Gasparri, Martina Lippi, Skander Moalla, Razvan Pascanu, and Çaǧlar Gülçehre.

The scientist's research explored the integration of distributed algorithms for task allocation and system coordination in networked environments, particularly focusing on multi-robot and multi-agent systems. They addressed problems related to coordination safety, system reference frames, and trust issues within reinforcement learning frameworks.

Best Publications

  • Sequential gradient-restoration algorithm for optimal control problems

    J. N. Damoulakis;A. Miele;R. E. Pritchard

  • Sequential gradient-restoration algorithm for the minimization of constrained functions - Ordinary and conjugate gradient versions

    A. Miele;H. Y. Huang;J. C. Heideman

  • General technique for solving nonlinear, two-point boundary-value problems via the method of particular solutions

    A. Miele;R. R. Iyer

  • Recent advances in gradient algorithms for optimal control problems

    A. Miele

  • On the method of multipliers for mathematical programming problems

    A. Miele;P. E. Moseley;A. V. Levy;G. M. Coggins

  • Sequential gradient-restoration algorithm for optimal control problems with general boundary conditions

    A. K. Wu;A. Miele

  • Optimal take-off trajectories in the presence of windshear

    A Miele;T Wang;W W Melvin

  • Method of particular solutions for linear, two-point boundary-value problems

    Angelo Miele

  • Study on a memory gradient method for the minimization of functions

    A. Miele;J. W. Cantrell

  • Sequential gradient-restoration algorithm for optimal control problems with nondifferential constraints

    A. Miele;J. N. Damoulakis;J. R. Cloutier;J. L. Tietze

  • Primal-dual properties of sequential gradient-restoration algorithms for optimal control problems 2. General problem

    A Miele;T Wang

  • Optimization and acceleration guidance of flight trajectories in a windshear

    A. Miele;T. Wang;W. W. Melvin

  • Sequential conjugate gradient-restoration algorithm for optimal control problems with non-differential constraints and general boundary conditions, part I

    Unknown

  • Guidance strategies for near-optimum take-off performance in a windshear

    A Miele;T Wang;W W Melvin

  • Gradient Algorithms for the Optimization of Dynamic Systems

    Angelo Miele

  • Use of the Augmented Penalty Function in Mathematical Programming Problems) Part 1

    A. Miele;E. E. Cragg;R. R. Iyer;A. V. Levy

  • OPTIMAL TRAJECTORIES FOR EARTH–MOON–EARTH FLIGHT

    A. Miele;S. Mancuso

  • Optimal abort landing trajectories in the presence of windshear

    A. Miele;T. Wang;C. Y. Tzeng;W. W. Melvin

  • Optimal Trajectories for Spacecraft Rendezvous

    A. Miele;M. W. Weeks;M. Ciarcià

  • Primal and dual formulations of sequential gradient-restoration algorithms for trajectory optimization problems

    A. Miele;T. Wang;V.K. Basapur

  • Multiple-Subarc Gradient-Restoration Algorithm, Part 1: Algorithm Structure

    A. Miele;T. Wang

  • The 1st John V. Breakwell Memorial Lecture: Recent advances in the optimization and guidance of aeroassisted orbital transfers☆☆☆

    A. Miele

  • Theorem of Image Trajectories in the Earth-Moon Space

    Angelo Miele

  • Acceleration, gamma, and theta guidance for abort landing in a windshear

    A. Miele;T. Wang;W. W. Melvin;R. L. Bowles

  • Gamma guidance schemes for flight in a windshear

    A. Miele;T. Wang;W. W. Melvin;R. L. Bowles

  • Use of the augmented penalty function in mathematical programming problems, part 2

    A. Miele;E. E. Cragg;A. V. Levy

  • Computing Methods in Optimization Problems

    G. Arienti;A. Colonelli Daneri;M. Auslender;E. J. Beltrami

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