World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
4542
World Ranking
11786
National Ranking
4819

Danilo Orlando publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Danilo Orlando sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 201 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Danilo Orlando D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Danilo Orlando sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 35 D-Index — 20th percentile

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

The last bar groups every scientist with 131 D-Index or more.

Overview

Danilo Orlando is affiliated with the IEEE Computer Society in the United States. Their research primarily spans the fields of Engineering and Computer Science, with a significant focus on Aerospace Engineering, Signal Processing, Electrical and Electronic Engineering, Artificial Intelligence, and Biomedical Engineering.

The main topics in their body of work include Radar Systems and Signal Processing, Advanced SAR Imaging Techniques, Direction-of-Arrival Estimation Techniques, Synthetic Aperture Radar (SAR) Applications and Techniques, Target Tracking and Data Fusion in Sensor Networks, Microwave Imaging and Scattering Analysis, and Distributed Sensor Networks and Detection Algorithms.

Frequent co-authors contributing to their research include Pia Addabbo, Chengpeng Hao, Gaetano Giunta, Carmine Clemente, and Filippo Biondi.

The scientist has published extensively in several venues, including:

  • IEEE Transactions on Aerospace and Electronic Systems
  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Signal Processing Letters
  • Signal Processing

Recent papers authored or co-authored by Danilo Orlando cover a range of topics in radar and signal processing. Notable publications include:

  • Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Learning Strategies for Radar Clutter Classification, 2021, CINECA IRIS Institutional Research Information System (University of Pisa)
  • Radar Adaptive Detection Architectures for Heterogeneous Environments, 2020, IEEE Transactions on Signal Processing
  • Adaptive Radar Detection and Classification Algorithms for Multiple Coherent Signals, 2020, IEEE Transactions on Signal Processing
  • Adaptive Radar Detection in the Presence of Multiple Alternative Hypotheses Using Kullback-Leibler Information Criterion-Part I: Detector Designs, 2021, IEEE Transactions on Signal Processing

Best Publications

  • Advanced Radar Detection Schemes Under Mismatched Signal Models

    Danilo Orlando;Francesco Bandiera;Giuseppe Ricci

  • Track-Before-Detect Strategies for STAP Radars

    D. Orlando;L. Venturino;M. Lops;G. Ricci

  • A Unifying Framework for Adaptive Radar Detection in Homogeneous Plus Structured Interference— Part II: Detectors Design

    Domenico Ciuonzo;Antonio De Maio;Danilo Orlando

  • Track-Before-Detect Algorithms for Targets with Kinematic Constraints

    D. Orlando;G. Ricci;Y. Bar-Shalom

  • Detection Algorithms to Discriminate Between Radar Targets and ECM Signals

    F Bandiera;A Farina;D Orlando;G Ricci

  • Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery.

    Jun Liu;Zengfu Hou;Wei Li;Ran Tao

  • A Unifying Framework for Adaptive Radar Detection in Homogeneous Plus Structured Interference— Part I: On the Maximal Invariant Statistic

    D. Ciuonzo;A. De Maio;D. Orlando

  • GLRT-Based Direction Detectors in Homogeneous Noise and Subspace Interference

    F. Bandiera;O. Besson;D. Orlando;G. Ricci

  • Adaptive Detection of Point-Like Targets in Spectrally Symmetric Interference

    Antonio De Maio;Danilo Orlando;Chengpeng Hao;Goffredo Foglia

  • On the Statistical Invariance for Adaptive Radar Detection in Partially Homogeneous Disturbance Plus Structured Interference

    Domenico Ciuonzo;Antonio De Maio;Danilo Orlando

  • Persymmetric Rao and Wald Tests for Partially Homogeneous Environment

    Chengpeng Hao;D. Orlando;Xiaochuan Ma;Chaohuan Hou

  • A Rao Test With Enhanced Selectivity Properties in Homogeneous Scenarios

    Danilo Orlando;Giuseppe Ricci

  • Adaptive Radar Detection of a Subspace Signal Embedded in Subspace Structured Plus Gaussian Interference Via Invariance

    Antonio De Maio;Danilo Orlando

  • Persymmetric adaptive detection of distributed targets in partially-homogeneous environment

    Chengpeng Hao;Danilo Orlando;Goffredo Foglia;Xiaochuan Ma

  • Diffuse Multipath Exploitation for Adaptive Radar Detection

    Augusto Aubry;Antonio De Maio;Goffredo Foglia;Danilo Orlando

  • An Invariant Approach to Adaptive Radar Detection Under Covariance Persymmetry

    Antonio De Maio;Danilo Orlando

  • Adaptive Radar Detection and Localization of a Point-Like Target

    D. Orlando;G. Ricci

  • Adaptive Detection of Point-Like Targets in the Presence of Homogeneous Clutter and Subspace Interference

    A. Aubry;A. De Maio;D. Orlando;M. Piezzo

  • CFAR detection of extended and multiple point-like targets without assignment of secondary data

    F. Bandiera;D. Orlando;G. Ricci

  • A Novel Noise Jamming Detection Algorithm for Radar Applications

    Danilo Orlando

  • Knowledge-Based Adaptive Detection: Joint Exploitation of Clutter and System Symmetry Properties

    Chengpeng Hao;Danilo Orlando;Goffredo Foglia;Gaetano Giunta

Frequent Co-Authors

Giuseppe Ricci
Giuseppe Ricci University of Salento
Antonio De Maio
Antonio De Maio University of Naples Federico II
Alfonso Farina
Alfonso Farina Finmeccanica (Italy)
Olivier Besson
Olivier Besson National Higher French Institute of Aeronautics and Space
Augusto Aubry
Augusto Aubry University of Naples Federico II
Domenico Ciuonzo
Domenico Ciuonzo University of Naples Federico II
Louis L. Scharf
Louis L. Scharf Colorado State University
Marco Lops
Marco Lops University of Naples Federico II
Giuseppe Bianchi
Giuseppe Bianchi University of Rome Tor Vergata
Hongbin Li
Hongbin Li Stevens Institute of Technology

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