World's Best Scientists 2026 revealed!
Miguel R. D. Rodrigues

Miguel R. D. Rodrigues

D-Index & Metrics

Computer Science

D-Index
30
Citations
6979
World Ranking
13866
National Ranking
885

Miguel R. D. Rodrigues 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 Miguel R. D. Rodrigues 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: 226 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Miguel R. D. Rodrigues 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 Miguel R. D. Rodrigues 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Miguel R. D. Rodrigues is affiliated with University College London in the United Kingdom. Their research predominantly spans Computer Science and Engineering, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Electrical and Electronic Engineering, and Biomedical Engineering.

The scientist's work involves multiple topics centered on machine learning and signal processing. Key areas include Sparse and Compressive Sensing Techniques, Adversarial Robustness in Machine Learning, Machine Learning and Algorithms, Machine Learning and Extreme Learning Machines (ELM), Neural Networks and Applications, Advanced Neural Network Applications, and Machine Learning and Data Classification.

Their recent publications cover a variety of technological and scientific problems, as reflected in papers such as:

  • Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules (2021, IEEE Transactions on Circuits and Systems for Video Technology)
  • FPGA-Based Acceleration for Bayesian Convolutional Neural Networks (2022, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems)
  • Neural network-based classification of X-ray fluorescence spectra of artists' pigments: an approach leveraging a synthetic dataset created using the fundamental parameters method (2022, Heritage Science)
  • ADMM-Based Hyperspectral Unmixing Networks for Abundance and Endmember Estimation (2021, IEEE Transactions on Geoscience and Remote Sensing)
  • Theoretical Perspectives on Deep Learning Methods in Inverse Problems (2022, IEEE Journal on Selected Areas in Information Theory)

Miguel R. D. Rodrigues has frequently published in venues such as arXiv, IEEE Transactions on Signal Processing, SSRN Electronic Journal, Environmental Data Science, and the International Journal of Pharmaceutics.

The scientist collaborates regularly with several coauthors, including Martin Ferianc, Gholamali Aminian, Laura Toni, Yonina C. Eldar, and Wei Pu.

Best Publications

  • Wireless Information-Theoretic Security

    M. Bloch;J. Barros;M.R.D. Rodrigues;S.W. McLaughlin

  • Secrecy Capacity of Wireless Channels

    Joao Barros;Miguel D. Rodrigues

  • Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules

    Jialong Xu;Bo Ai;Wei Chen;Ang Yang

  • Robust Large Margin Deep Neural Networks

    Jure Sokolic;Raja Giryes;Guillermo Sapiro;Miguel R. D. Rodrigues

  • MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation

    F. Perez-Cruz;M.R.D. Rodrigues;S. Verdu

  • Spectrally Efficient FDM Signals: Bandwidth Gain at the Expense of Receiver Complexity

    I. Kanaras;A. Chorti;M. R. D. Rodrigues;I. Darwazeh

  • Compressed Sensing With Prior Information: Strategies, Geometry, and Bounds

    Joao F. C. Mota;Nikos Deligiannis;Miguel R. D. Rodrigues

  • Generalization Error in Deep Learning

    Daniel Jakubovitz;Raja Giryes;Miguel R. D. Rodrigues

  • Multimodal Image Super-Resolution via Joint Sparse Representations Induced by Coupled Dictionaries

    Pingfan Song;Xin Deng;Joao F. C. Mota;Nikos Deligiannis

  • On Wireless Channels With ${M}$ -Antenna Eavesdroppers: Characterization of the Outage Probability and $ arepsilon $ -Outage Secrecy Capacity

    Vinay Uday Prabhu;Miguel R. D. Rodrigues

  • Projection Design for Statistical Compressive Sensing: A Tight Frame Based Approach

    Wei Chen;M. R. D. Rodrigues;I. J. Wassell

  • COMMUNICATIONS-INSPIRED PROJECTION DESIGN WITH APPLICATION TO COMPRESSIVE SENSING

    William R. Carson;William R. Carson;Minhua Chen;Miguel R. D. Rodrigues;A. Robert Calderbank

  • On the Use of Unit-Norm Tight Frames to Improve the Average MSE Performance in Compressive Sensing Applications

    Wei Chen;M. R. D. Rodrigues;I. J. Wassell

  • Hardware-Limited Task-Based Quantization

    Nir Shlezinger;Yonina C. Eldar;Miguel R. D. Rodrigues

  • Coupled Dictionary Learning for Multi-Contrast MRI Reconstruction

    Pingfan Song;Lior Weizman;Joao F. C. Mota;Yonina C. Eldar

  • Comparison of Convolutional and Turbo Coding for Broadband FWA Systems

    I.A. Chatzigeorgiou;M.R.D. Rodrigues;I.J. Wassell;R.A. Carrasco

  • Joint channel equalization and detection of Spectrally Efficient FDM signals

    Arsenia Chorti;Ioannis Kanaras;Miguel R.D. Rodrigues;Izzat Darwazeh

  • FPGA-Based Acceleration for Bayesian Convolutional Neural Networks

    Unknown

  • Asymptotic Task-Based Quantization With Application to Massive MIMO

    Nir Shlezinger;Yonina C. Eldar;Miguel R. D. Rodrigues

  • Reconstruction of Signals Drawn From a Gaussian Mixture Via Noisy Compressive Measurements

    Francesco Renna;Robert Calderbank;Lawrence Carin;Miguel R. D. Rodrigues

  • Adversarially Learned Representations for Information Obfuscation and Inference

    Martín Bertrán;Natalia Martínez;Afroditi Papadaki;Qiang Qiu

  • Filter Design With Secrecy Constraints: The MIMO Gaussian Wiretap Channel

    Hugo Reboredo;Joao Xavier;Miguel R. D. Rodrigues

  • Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Features in the Presence of Side Information

    Francesco Renna;Liming Wang;Xin Yuan;Jianbo Yang

  • Margin Preservation of Deep Neural Networks.

    Jure Sokolic;Raja Giryes;Guillermo Sapiro;Miguel R. D. Rodrigues

Frequent Co-Authors

Lawrence Carin
Lawrence Carin Duke University
Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science
Izzat Darwazeh
Izzat Darwazeh University College London
Guillermo Sapiro
Guillermo Sapiro Princeton University
Raja Giryes
Raja Giryes Tel Aviv University
Ingrid Daubechies
Ingrid Daubechies Duke University
Xin Yuan
Xin Yuan Nanyang Technological University
Wayne Luk
Wayne Luk Imperial College London
Joao Barros
Joao Barros University of Porto
Volkan Cevher
Volkan Cevher École Polytechnique Fédérale de Lausanne

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

Exploring computer science in the USA opens doors to a variety of related educational and career options. For those seeking rapid entry into the tech workforce, there are certificate programs that pay well. These certifications often focus on in-demand skills and can lead to lucrative tech roles without the commitment of a full degree.

If you’re interested in advancing your career further, consider the fastest masters degree online options. These accelerated programs allow working professionals to upskill quickly in high-growth areas of computer science and IT.

Choosing from the most useful masters degrees can also boost your competitiveness in the ever-evolving tech job market. Courses in areas like data science, cybersecurity, and software engineering remain especially sought-after by employers.

For those starting out or seeking a flexible foundation, an associates degree online in computer science or information technology can be an effective stepping stone. These programs often transfer easily to bachelor’s degrees or lead directly to entry-level tech positions.

Best Scientists Citing Miguel R. D. Rodrigues

Trending Scientists