World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
6730
World Ranking
7298
National Ranking
85

Darko Zibar 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 Darko Zibar 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: 424 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Darko Zibar 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 Darko Zibar 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: 40 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Darko Zibar is affiliated with the Technical University of Denmark in Denmark. Their research spans multiple key areas within engineering and computer science, with a primary focus on electrical and electronic engineering, artificial intelligence, and atomic and molecular physics, and optics.

Their work covers various specialized topics, including:

  • Optical Network Technologies
  • Photonic and Optical Devices
  • Neural Networks and Reservoir Computing
  • Advanced Fiber Laser Technologies
  • Advanced Photonic Communication Systems
  • Semiconductor Lasers and Optical Devices
  • Advanced Fiber Optic Sensors

Darko Zibar has contributed to academic literature with publications in notable venues. Frequent publication venues are:

  • arXiv (Cornell University)
  • Journal of Lightwave Technology
  • Optics Express
  • Optics Letters
  • IEEE Photonics Technology Letters

Among the recent papers authored or coauthored by them are:

  • "Model-Aided Deep Learning Method for Path Loss Prediction in Mobile Communication Systems at 2.6 GHz," 2020, IEEE Access
  • "Machine learning aided carrier recovery in continuous-variable quantum key distribution," 2021, npj Quantum Information
  • "End-to-End Optimization of Coherent Optical Communications Over the Split-Step Fourier Method Guided by the Nonlinear Fourier Transform Theory," 2020, Journal of Lightwave Technology
  • "Reservoir-Computing Based Equalization With Optical Pre-Processing for Short-Reach Optical Transmission," 2020, IEEE Journal of Selected Topics in Quantum Electronics
  • "Introducing Load Aware Neural Networks for Accurate Predictions of Raman Amplifiers," 2020, Journal of Lightwave Technology

Their frequent coauthors include Francesco Da Ros, Ognjen Jovanovic, Metodi P. Yankov, Andrea Carena, and Uiara Celine de Moura. Collaboration with these researchers reflects a focus on topics related to photonics, optical communications, and neural computing systems.

Best Publications

  • An Overview on Application of Machine Learning Techniques in Optical Networks

    Francesco Musumeci;Cristina Rottondi;Avishek Nag;Irene Macaluso

  • 100 Gbit/s hybrid optical fiber-wireless link in the W-band (75-110 GHz).

    Xiaodan Pang;Antonio Caballero;Anton Dogadaev;Valeria Arlunno

  • Single-source chip-based frequency comb enabling extreme parallel data transmission

    Hao Hu;Francesco Da Ros;Minhao Pu;Feihong Ye

  • Machine Learning Techniques in Optical Communication

    Darko Zibar;Molly Piels;Rasmus Jones;Christian G. Schaeffer

  • Model-Aided Deep Learning Method for Path Loss Prediction in Mobile Communication Systems at 2.6 GHz

    Jakob Thrane;Darko Zibar;Henrik Lehrmann Christiansen

  • Machine Learning Techniques for Optical Performance Monitoring From Directly Detected PDM-QAM Signals

    Jakob Thrane;Jesper Wass;Molly Piels;Julio C. M. Diniz

  • Constellation Shaping for Fiber-Optic Channels With QAM and High Spectral Efficiency

    Metodi P. Yankov;Darko Zibar;Knud J. Larsen;Lars P. B. Christensen

  • 0.4 THz Photonic-Wireless Link With 106 Gb/s Single Channel Bitrate

    Shi Jia;Xiaodan Pang;Oskars Ozolins;Xianbin Yu

  • Dual-polarization nonlinear Fourier transform-based optical communication system

    S. Gaiarin;A. M. Perego;E. P. da Silva;F. Da Ros

  • Constellation Shaping for WDM Systems Using 256QAM/1024QAM With Probabilistic Optimization

    Metodi P. Yankovn;Francesco Da Ros;Edson P. da Silva;Soren Forchhammer

  • Widely Linear Equalization for IQ Imbalance and Skew Compensation in Optical Coherent Receivers

    Edson Porto da Silva;Darko Zibar

  • High-Capacity Wireless Signal Generation and Demodulation in 75- to 110-GHz Band Employing All-Optical OFDM

    D Zibar;R Sambaraju;A Caballero;J Herrera

  • Inverse System Design Using Machine Learning: The Raman Amplifier Case

    Darko Zibar;Ann Margareth Rosa Brusin;Uiara C. de Moura;Francesco Da Ros

  • Nonlinear impairment compensation using expectation maximization for dispersion managed and unmanaged PDM 16-QAM transmission

    Darko Zibar;Ole Winther;Niccolo Franceschi;Robert Borkowski

  • Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers

    Robert Borkowski;Darko Zibar;Antonio Caballero;Valeria Arlunno

  • Multi–Band Programmable Gain Raman Amplifier

    Uiara Celine de Moura;Asif Iqbal;Morteza Kamalian;Lukasz Krzczanowicz

  • 25 Gbit/s QPSK Hybrid Fiber-Wireless Transmission in the W-Band (75–110 GHz) With Remote Antenna Unit for In-Building Wireless Networks

    Xiaodan Pang;A. Caballero;A. Dogadaev;V. Arlunno

  • Deep Learning of Geometric Constellation Shaping Including Fiber Nonlinearities

    Rasmus T. Jones;Tobias A. Eriksson;Metodi P. Yankov;Darko Zibar

  • 100 GHz Externally Modulated Laser for Optical Interconnects

    Oskars Ozolins;Xiaodan Pang;Miguel Iglesias Olmedo;Aditya Kakkar

  • Machine learning under the spotlight

    Darko Zibar;Henk Wymeersch;Ilya Lyubomirsky

  • Machine learning aided carrier recovery in continuous-variable quantum key distribution

    Hou-Man Chin;Nitin Jain;Darko Zibar;Ulrik L. Andersen

  • Digital Coherent Receiver for Phase-Modulated Radio-Over-Fiber Optical Links

    D. Zibar;Xianbin Yu;C. Peucheret;P. Jeppesen

  • 260 Gbit/s photonic-wireless link in the THz band

    X. Pang;S. Jia;O. Ozolins;X. Yu

  • Dual polarization nonlinear Fourier transform-based optical communication system

    Simone Gaiarin;Auro Michele Perego;Edson Porto da Silva;Francesco Da Ros

Frequent Co-Authors

Idelfonso Tafur Monroy
Idelfonso Tafur Monroy Eindhoven University of Technology
Leif Katsuo Oxenløwe
Leif Katsuo Oxenløwe Technical University of Denmark
Michael Galili
Michael Galili Technical University of Denmark
Xianbin Yu
Xianbin Yu Zhejiang University
Sergei Popov
Sergei Popov Royal Institute of Technology
Andrea Carena
Andrea Carena Polytechnic University of Turin
Gunnar Jacobsen
Gunnar Jacobsen Royal Institute of Technology
Jesper Mørk
Jesper Mørk Technical University of Denmark
John E. Bowers
John E. Bowers University of California, Santa Barbara
Mark J. W. Rodwell
Mark J. W. Rodwell University of California, Santa Barbara

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