World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
10392
World Ranking
6426
National Ranking
2864

Overview

Kenneth Zeger is affiliated with the University of California, San Diego in the United States. Their research primarily lies within the field of Computer Science, with a focus on several specialized subfields and topics.

The main subfields of study for Kenneth Zeger include:

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Molecular Biology
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

The scientist's research themes encompass the following areas:

  • Algorithms and Data Compression
  • Cellular Automata and Applications
  • Theoretical and Computational Physics
  • VLSI and FPGA Design Techniques
  • Parallel Computing and Optimization Techniques
  • Coding theory and cryptography
  • Semigroups and automata theory

Kenneth Zeger has published multiple papers, with a notable concentration in the IEEE Transactions on Information Theory and arXiv (Cornell University). Recent publications include:

  • Competitive Advantage of Huffman and Shannon-Fano Codes, 2024, IEEE Transactions on Information Theory
  • Hexagonal Run-Length Zero Capacity Region-Part I: Analytical Proofs, 2021, IEEE Transactions on Information Theory
  • Hexagonal Run-Length Zero Capacity Region-Part II: Automated Proofs, 2021, IEEE Transactions on Information Theory
  • The 3/4 Conjecture for Fix-Free Codes With at Most Three Distinct Codeword Lengths, 2022, IEEE Transactions on Information Theory
  • Competitive Advantage of Huffman and Shannon-Fano Codes, 2023, arXiv (Cornell University)

The frequent coauthor associated with Kenneth Zeger is Spencer Congero, contributing to multiple joint publications.

Throughout their career, Kenneth Zeger has consistently contributed to journals focusing on information theory and related computational topics.

Best Publications

  • Closest point search in lattices

    E. Agrell;T. Eriksson;A. Vardy;K. Zeger

  • Insufficiency of linear coding in network information flow

    R. Dougherty;C. Freiling;K. Zeger

  • Pseudo-Gray coding

    K. Zeger;A. Gersho

  • Learning and design of principal curves

    B. Kegl;A. Krzyzak;T. Linder;K. Zeger

  • Progressive image coding for noisy channels

    P.G. Sherwood;K. Zeger

  • Networks, Matroids, and Non-Shannon Information Inequalities

    R. Dougherty;C. Freiling;K. Zeger

  • Error protection for progressive image transmission over memoryless and fading channels

    P.G. Sherwood;K. Zeger

  • Progressive image coding on noisy channels

    P.G. Sherwood;K. Zeger

  • Competitive learning and soft competition for vector quantizer design

    E. Yair;K. Zeger;A. Gersho

  • Upper bounds for constant-weight codes

    E. Agrell;A. Vardy;K. Zeger

  • Tradeoff between source and channel coding

    B. Hochwald;K. Zeger

  • Globally optimal vector quantizer design by stochastic relaxation

    K. Zeger;J. Vaisey;A. Gersho

  • Six New Non-Shannon Information Inequalities

    R. Dougherty;C. Freiling;K. Zeger

  • On the capacity of two-dimensional run-length constrained channels

    A. Kato;K. Zeger

  • Nonparametric estimation via empirical risk minimization

    G. Lugosi;K. Zeger

  • Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding

    T. Linder;G. Lugosi;K. Zeger

  • Combined forward error control and packetized zerotree wavelet encoding for transmission of images over varying channels

    P.C. Cosman;J.K. Rogers;P.G. Sherwood;K. Zeger

  • Network routing capacity

    J. Cannons;R. Dougherty;C. Freiling;K. Zeger

  • Nonreversibility and Equivalent Constructions of Multiple-Unicast Networks

    R. Dougherty;K. Zeger

  • Unachievability of network coding capacity

    Randall Dougherty;Chris Freiling;Kenneth Zeger

Frequent Co-Authors

Tamas Linder
Tamas Linder Queen's University
Allen Gersho
Allen Gersho University of California, Santa Barbara
Gábor Lugosi
Gábor Lugosi Pompeu Fabra University
Massimo Franceschetti
Massimo Franceschetti University of California, San Diego
Alexander Vardy
Alexander Vardy University of California, San Diego
Pamela C. Cosman
Pamela C. Cosman University of California, San Diego
Michelle Effros
Michelle Effros California Institute of Technology
Erik Agrell
Erik Agrell Chalmers University of Technology
Ram Zamir
Ram Zamir Tel Aviv University

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