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Computer Science

D-Index
43
Citations
7744
World Ranking
7989
National Ranking
129

Nir Shlezinger 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 Nir Shlezinger 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: 289 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Nir Shlezinger 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 Nir Shlezinger 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Nir Shlezinger is affiliated with Ben-Gurion University of the Negev in Israel. Their research spans multiple domains within engineering and computer science, with a significant focus on electrical and electronic engineering, artificial intelligence, aerospace engineering, signal processing, and computer networks and communications.

Their scholarly work frequently appears in notable publication venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Wireless Communications
  • IEEE Transactions on Vehicular Technology
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The topics addressed in their research cover a broad spectrum of advanced technologies, such as:

  • Antenna Design and Analysis
  • Advanced Wireless Communication Technologies
  • Target Tracking and Data Fusion in Sensor Networks
  • Energy Harvesting in Wireless Networks
  • Millimeter-Wave Propagation and Modeling
  • Advanced MIMO Systems Optimization
  • Indoor and Outdoor Localization Technologies

Some of their recent papers emphasize developments in signal processing, wireless communications, and neural network applications. Key publications include:

  • Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar, 2020, IEEE Transactions on Signal Processing
  • KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics, 2022, IEEE Transactions on Signal Processing
  • Beam Focusing for Near-Field Multiuser MIMO Communications, 2022, IEEE Transactions on Wireless Communications
  • Communication-efficient federated learning, 2021, Proceedings of the National Academy of Sciences
  • Model-Based Deep Learning, 2023, Proceedings of the IEEE

Their collaborations include frequent co-authorship with various researchers, among whom are:

  • Yonina C. Eldar
  • Guy Revach
  • Ruud J. G. van Sloun
  • George C. Alexandropoulos
  • Mohammadreza F. Imani

Shlezinger's body of work combines theoretical advances with applications in wireless communication systems and signal processing, leveraging machine learning approaches and optimization techniques to address challenges in multiuser MIMO systems, federated learning, and adaptive filtering under uncertain dynamics.

Best Publications

  • Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar

    Xiang Liu;Tianyao Huang;Nir Shlezinger;Yimin Liu

  • KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics.

    Guy Revach;Nir Shlezinger;Xiaoyong Ni;Adria Lopez Escoriza

  • Beam Focusing for Near-Field Multi-User MIMO Communications

    Haiyang Zhang;Nir Shlezinger;Francesco Guidi;Davide Dardari

  • Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies

    Dingyou Ma;Nir Shlezinger;Tianyao Huang;Yimin Liu

  • Communication-efficient federated learning.

    Mingzhe Chen;Mingzhe Chen;Nir Shlezinger;H. Vincent Poor;Yonina C. Eldar

  • Model-Based Deep Learning.

    Nir Shlezinger;Jay Whang;Yonina C. Eldar;Alexandros G. Dimakis

  • 6G Wireless Communications: From Far-Field Beam Steering to Near-Field Beam Focusing

    Unknown

  • Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications

    Nir Shlezinger;George C. Alexandropoulos;Mohammadreza F. Imani;Yonina C. Eldar

  • MAJoRCom: A Dual-Function Radar Communication System Using Index Modulation

    Tianyao Huang;Nir Shlezinger;Xingyu Xu;Yimin Liu

  • UVeQFed: Universal Vector Quantization for Federated Learning

    Nir Shlezinger;Mingzhe Chen;Yonina C. Eldar;H. Vincent Poor

  • Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization

    Unknown

  • Over-the-Air Federated Learning From Heterogeneous Data

    Tomer Sery;Nir Shlezinger;Kobi Cohen;Yonina Eldar

  • Federated Learning: A Signal Processing Perspective.

    Tomer Gafni;Nir Shlezinger;Kobi Cohen;Yonina C. Eldar

  • Reconfigurable Intelligent Surfaces for Rich Scattering Wireless Communications: Recent Experiments, Challenges, and Opportunities

    George C. Alexandropoulos;Nir Shlezinger;Philipp del Hougne

  • Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing

    Unknown

  • ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection

    Nir Shlezinger;Nariman Farsad;Yonina C. Eldar;Andrea J. Goldsmith

  • A reconfigurable intelligent surface with integrated sensing capability.

    Idban Alamzadeh;George C. Alexandropoulos;Nir Shlezinger;Mohammadreza F. Imani

  • PhysFad: Physics-Based End-to-End Channel Modeling of RIS-Parametrized Environments With Adjustable Fading

    Unknown

  • Dynamic Metasurface Antennas for Uplink Massive MIMO Systems

    Nir Shlezinger;Or Dicker;Yonina C. Eldar;Insang Yoo

  • Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications.

    George C. Alexandropoulos;Nir Shlezinger;Idban Alamzadeh;Mohammadreza F. Imani

  • Federated Learning with Quantization Constraints

    Nir Shlezinger;Mingzhe Chen;Yonina C. Eldar;H. Vincent Poor

  • Near-field Wireless Power Transfer for 6G Internet-of-Everything Mobile Networks: Opportunities and Challenges

    Haiyang Zhang;Nir Shlezinger;Francesco Guidi;Davide Dardari

  • DeepSIC: Deep Soft Interference Cancellation for Multiuser MIMO Detection

    Nir Shlezinger;Rong Fu;Yonina C. Eldar

  • Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype

    Dingyou Ma;Nir Shlezinger;Tianyao Huang;Yariv Shavit

  • A Block Sparsity Based Estimator for mmWave Massive MIMO Channels With Beam Squint

    Mingjin Wang;Feifei Gao;Nir Shlezinger;Mark F. Flanagan

  • Dynamic Metasurface Antennas for MIMO-OFDM Receivers With Bit-Limited ADCs

    Hanqing Wang;Nir Shlezinger;Yonina C. Eldar;Shi Jin

  • FRaC: FMCW-Based Joint Radar-Communications System via Index Modulation

    Dingyou Ma;Nir Shlezinger;Tianyao Huang;Yimin Liu

  • Hardware-Limited Task-Based Quantization

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

Frequent Co-Authors

Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science
Mohammadreza F. Imani
Mohammadreza F. Imani Arizona State University
Andrea Goldsmith
Andrea Goldsmith Stony Brook University
David R. Smith
David R. Smith Duke University
George C. Alexandropoulos
George C. Alexandropoulos National and Kapodistrian University of Athens
H. Vincent Poor
H. Vincent Poor Princeton University
Mingzhe Chen
Mingzhe Chen University of Miami
Davide Dardari
Davide Dardari University of Bologna
Shuguang Cui
Shuguang Cui Chinese University of Hong Kong, Shenzhen

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