World's Best Scientists 2026 revealed!
David A. Castanon

David A. Castanon

D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
6196
World Ranking
8640
National Ranking
2400

David A. Castanon 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 David A. Castanon 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: 260 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

David A. Castanon 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 David A. Castanon 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.

Research.com Recognitions

  • 2019 - IEEE Fellow For contributions to discrete-time stochastic control and information fusion

Overview

David A. Castanon is affiliated with Boston University in the United States. Their research spans multiple domains related to computer science and medicine, with a focus on imaging and sensor networks.

The scientist's main fields of study include:

  • Computer Science
  • Medicine

Their work also extends into several subfields, including:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Networks and Communications
  • Biomedical Engineering
  • Artificial Intelligence
  • Radiation

Key topics covered in their publications are:

  • Advanced X-ray and CT Imaging
  • Medical Imaging Techniques and Applications
  • Radiation Dose and Imaging
  • Artificial Intelligence in Games
  • Nuclear Physics and Applications
  • Distributed Sensor Networks and Detection Algorithms
  • Energy Efficient Wireless Sensor Networks

Recent papers authored or co-authored by David A. Castanon include:

  • "Enhanced Material Estimation with Multi-Spectral CT," 2021, Electronic Imaging
  • "Material Identification in Presence of Metal for Baggage Screening," 2020, Electronic Imaging
  • "Stochastic Event-based Sensor Schedules for Remote State Estimation in Cognitive Radio Sensor Networks," 2020, arXiv (Cornell University)
  • "Dynamic Network Flow Optimization for Task Scheduling in PTZ Camera Surveillance Systems," 2025, arXiv (Cornell University)

Frequent co-authors of David A. Castanon are:

  • Sandamali Devadithya
  • Lingying Huang
  • Wang Jia-zheng
  • Enoch Kung
  • Yilin Mo

Publication venues where they have often contributed include:

  • Electronic Imaging
  • arXiv (Cornell University)

David A. Castanon was recognized as an IEEE Fellow in 2019 for contributions to discrete-time stochastic control and information fusion.

Best Publications

  • The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight

    M. Athans;D. Castanon;K. Dunn;C. Greene

  • Rollout Algorithms for Stochastic Scheduling Problems

    Dimitri P. Bertsekas;David A. Castanon

  • Combining and updating of local estimates and regional maps along sets of one-dimensional tracks

    A. Willsky;M. Bello;D. Castanon;B. Levy

  • Discrete-time Markovian-jump linear quadratic optimal control

    H. J. Chizeck;A. S. Willsky;D. Castanon

  • The auction algorithm for the transportation problem

    D. P. Bertsekas;D. A. Castanon

  • Parallel synchronous and asynchronous implementations of the auction algorithm

    Dimitri P. Bertsekas;David A. Castañon

  • Adaptive aggregation methods for infinite horizon dynamic programming

    D.P. Bertsekas;D.A. Castanon

  • Approximate dynamic programming for sensor management

    D.A. Castanon

  • CONTINUOUS-MEMBRANE SURFACE-MICROMACHINED SILICON DEFORMABLE MIRROR

    T. G. Bifano;Raji Krishnamoorthy Mali;J. K. Dorton;J. Perreault

  • Distributed estimation algorithms for nonlinear systems

    D. Castanon;D. Teneketzis

  • A forward/reverse auction algorithm for asymmetric assignment problems

    Dimitri P. Bertsekas;David A. Castañon

  • Optimal search strategies in dynamic hypothesis testing

    D.A. Castanon

  • Receding Horizon Planning for Dubins Traveling Salesman Problems

    Xiang Ma;D.A. Castanon

  • Efficient algorithms for finding the K best paths through a trellis

    D.A. Castanon

  • Feature enhancement and ATR performance using nonquadratic optimization-based SAR imaging

    M. Cetin;W.C. Karl;D.A. Castanon

  • Reverse Auction and the Solution of Inequality Constrained Assignment Problems

    Dimitri P. Bertsekas;David A. Castañon;Haralampos Tsaknakis

  • Hierarchical aggregation of singularly perturbed finite state Markov processes

    M. Coderch;A. S. Willsky;S. S. Sastry;D. A. Castanon

  • Efficient Sensor Management Policies for Distributed Target Tracking in Multihop Sensor Networks

    S. Aeron;V. Saligrama;D.A. Castaon

  • A scattering framework for decentralized estimation problems

    Bernard C. Levy;David A. Castañon;George C. Verghese;Alan S. Willsky

  • Robustness and modeling error characterization

    N. Lehtomaki;D. Castanon;B. Levy;G. Stein

Frequent Co-Authors

William Clement Karl
William Clement Karl Boston University
Venkatesh Saligrama
Venkatesh Saligrama Boston University
Dimitri P. Bertsekas
Dimitri P. Bertsekas Arizona State University
Bernard C. Levy
Bernard C. Levy University of California, Davis
Demosthenis Teneketzis
Demosthenis Teneketzis University of Michigan–Ann Arbor
Mujdat Cetin
Mujdat Cetin University of Rochester
Michael Athans
Michael Athans Instituto Superior Técnico
Peter B. Luh
Peter B. Luh University of Connecticut
Christos G. Cassandras
Christos G. Cassandras Boston University

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