World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
94
Citations
41671
World Ranking
247
National Ranking
126

Computer Science

D-Index
104
Citations
45737
World Ranking
309
National Ranking
170

Kannan Ramchandran publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Kannan Ramchandran sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 480 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Kannan Ramchandran D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Kannan Ramchandran sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 94 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2017 - IEEE Koji Kobayashi Computers and Communications Award “For pioneering contributions to the theory and practice of distributed source and storage coding.”

Overview

Kannan Ramchandran is affiliated with the University of California, Berkeley in the United States. Their research contributions span primarily across the field of Computer Science, with a particular focus on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Molecular Biology, and Electrical and Electronic Engineering.

The scientist's work encompasses a number of specific topics, including:

  • Advanced Bandit Algorithms Research
  • Stochastic Gradient Optimization Techniques
  • Privacy-Preserving Technologies in Data
  • Machine Learning and Algorithms
  • Machine Learning and ELM
  • Smart Grid Energy Management
  • Sparse and Compressive Sensing Techniques

Recent notable publications by Ramchandran include:

  • "An Efficient Framework for Clustered Federated Learning," 2022, IEEE Transactions on Information Theory
  • "FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning," 2020, arXiv (Cornell University)
  • "Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models," 2021, 2021 IEEE International Conference on Big Data (Big Data)
  • "Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions," 2021, Nature Communications
  • "Neurotoxin: Durable Backdoors in Federated Learning," 2022, arXiv (Cornell University)

Their frequent co-authors include:

  • Avishek Ghosh
  • Nived Rajaraman
  • Yaoqing Yang
  • Michael W. Mahoney
  • Abishek Sankararaman

Ramchandran's research has been published extensively in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Information Theory
  • 2021 IEEE International Conference on Big Data (Big Data)
  • Nature Communications
  • Management Science

In 2017, Kannan Ramchandran received the IEEE Koji Kobayashi Computers and Communications Award with the citation stating the recognition was "for pioneering contributions to the theory and practice of distributed source and storage coding."

Best Publications

  • Network Coding for Distributed Storage Systems

    A G Dimakis;P B Godfrey;Yunnan Wu;M J Wainwright

  • Network Coding for Distributed Storage Systems

    A.G. Dimakis;P.B. Godfrey;M.J. Wainwright;K. Ramchandran

  • Distributed source coding using syndromes (DISCUS): design and construction

    S.S. Pradhan;K. Ramchandran

  • Rate-distortion methods for image and video compression

    A. Ortega;K. Ramchandran

  • Low-complexity image denoising based on statistical modeling of wavelet coefficients

    M. Kivanc Mihcak;I. Kozintsev;K. Ramchandran;P. Moulin

  • Best wavelet packet bases in a rate-distortion sense

    K. Ramchandran;M. Vetterli

  • Speeding Up Distributed Machine Learning Using Codes

    Kangwook Lee;Maximilian Lam;Ramtin Pedarsani;Dimitris Papailiopoulos

  • A Survey on Network Codes for Distributed Storage

    A G Dimakis;K Ramchandran;Yunnan Wu;Changho Suh

  • Distributed compression in a dense microsensor network

    S.S. Pradhan;J. Kusuma;K. Ramchandran

  • Multiplexed coded illumination for Fourier Ptychography with an LED array microscope.

    Lei Tian;Xiao Li;Kannan Ramchandran;Laura Waller

  • Space-frequency quantization for wavelet image coding

    Zixiang Xiong;K. Ramchandran;M.T. Orchard

  • Bit allocation for dependent quantization with applications to multiresolution and MPEG video coders

    K. Ramchandran;A. Ortega;M. Vetterli

  • Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

    Dong Yin;Yudong Chen;Kannan Ramchandran;Peter L. Bartlett

  • Computationally efficient optimal power allocation algorithm for multicarrier communication systems

    B.S. Krongold;K. Ramchandran;D.L. Jones

  • Computationally efficient optimal power allocation algorithms for multicarrier communication systems

    B.S. Krongold;K. Ramchandran;D.L. Jones

  • Detecting primary receivers for cognitive radio applications

    B. Wild;K. Ramchandran

  • Multiresolution broadcast for digital HDTV using joint source/channel coding

    K. Ramchandran;A. Ortega;K.M. Uz;M. Vetterli

  • On compressing encrypted data

    M. Johnson;P. Ishwar;V. Prabhakaran;D. Schonberg

  • Multiple description source coding using forward error correction codes

    R. Puri;K. Ramchandran

  • Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising

    M. Kivanc Mihcak;I. Kozintsev;K. Ramchandran

  • Network Coding for Distributed Storage Systems

    Alexandros G. Dimakis;P. Brighten Godfrey;Martin J. Wainwright;Kannan Ramchandran

  • A Survey on Network Codes for Distributed Storage In distributed storage systems where reliability is maintained using erasure coding, network codes can be designed to meet specific requirements.

    Alexandros G. Dimakis;Kannan Ramchandran;Yunnan Wu;Changho Suh

Frequent Co-Authors

Nihar B. Shah
Nihar B. Shah Carnegie Mellon University
Martin Vetterli
Martin Vetterli École Polytechnique Fédérale de Lausanne
Michael T. Orchard
Michael T. Orchard Rice University
Zixiang Xiong
Zixiang Xiong Texas A&M University
Prakash Ishwar
Prakash Ishwar Boston University
Douglas L. Jones
Douglas L. Jones University of Illinois at Urbana-Champaign
Upamanyu Madhow
Upamanyu Madhow University of California, Santa Barbara
P. Vijay Kumar
P. Vijay Kumar Indian Institute of Science
Salim El Rouayheb
Salim El Rouayheb Rutgers, The State University of New Jersey

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