World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

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

Electronics and Electrical Engineering

D-Index
94
Citations
41671
World Ranking
247
National Ranking
125

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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