World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
11870
World Ranking
3292
National Ranking
1593

Research.com Recognitions

  • 2008 - Member of the National Academy of Engineering For the invention and development of advanced coding techniques for digital recording systems.
  • 1997 - IEEE Fellow For contributions to signal processing and coding for storage systems

Overview

Paul H. Siegel is affiliated with the University of California, San Diego in the United States. Their research spans multiple fields, primarily focusing on computer science and biochemistry, genetics, and molecular biology.

Their main fields of study include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

Their work covers several subfields within these disciplines, including:

  • Computer Networks and Communications
  • Molecular Biology
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering

Key topics of Paul H. Siegel's research involve:

  • Cellular Automata and Applications
  • DNA and Biological Computing
  • Error Correcting Code Techniques
  • Advanced Data Storage Technologies
  • Algorithms and Data Compression
  • Advanced biosensing and bioanalysis techniques
  • Advanced Wireless Communication Techniques

Siegel has been published in various venues with multiple contributions, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Information Theory
  • IEEE Transactions on Communications
  • IEEE Transactions on Molecular Biological and Multi-Scale Communications
  • IEEE Journal on Selected Areas in Information Theory

Frequent collaborators include:

  • Eitan Yaakobi
  • Simeng Zheng
  • Yi Liu
  • Andreas Lenz
  • Pengfei Huang

Recent notable publications by Paul H. Siegel comprise:

  • "Functional Error Correction for Robust Neural Networks," 2020, IEEE Journal on Selected Areas in Information Theory
  • "Survey for a Decade of Coding for DNA Storage," 2024, IEEE Transactions on Molecular Biological and Multi-Scale Communications
  • "PR-NN: RNN-Based Detection for Coded Partial-Response Channels," 2020, IEEE Journal on Selected Areas in Communications
  • "Rate-Constrained Shaping Codes for Structured Sources," 2020, IEEE Transactions on Information Theory
  • "A New Version of q-Ary Varshamov-Tenengolts Codes With More Efficient Encoders: The Differential VT Codes and The Differential Shifted VT Codes," 2024, IEEE Transactions on Information Theory

Throughout their career, Paul H. Siegel has received recognition including:

  • Member of the National Academy of Engineering (2008) for the invention and development of advanced coding techniques for digital recording systems
  • IEEE Fellow (1997) for contributions to signal processing and coding for storage systems

Best Publications

  • Characterizing flash memory: anomalies, observations, and applications

    Laura M. Grupp;Adrian M. Caulfield;Joel Coburn;Steven Swanson

  • Performance analysis and code optimization of low density parity-check codes on Rayleigh fading channels

    Jilei Hou;P.H. Siegel;L.B. Milstein

  • Capacity-approaching bandwidth-efficient coded modulation schemes based on low-density parity-check codes

    J. Hou;P.H. Siegel;L.B. Milstein;H.D. Pfister

  • Finite-state modulation codes for data storage

    B.H. Marcus;P.H. Siegel;J.K. Wolf

  • On the achievable information rates of finite state ISI channels

    H.D. Pfister;J.B. Soriaga;P.H. Siegel

  • Codes for digital recorders

    K.E. Schouhamer Immink;P.H. Siegel;J.K. Wolf

  • Matched Spectral Null Codes for Partial Response Channels

    R. Karabed;P.H. Siegel

  • Recording codes for digital magnetic storage

    P. Siegel

  • Windowed Decoding of Protograph-Based LDPC Convolutional Codes Over Erasure Channels

    A. R. Iyengar;M. Papaleo;P. H. Siegel;J. K. Wolf

  • Modulation and coding for information storage

    P.H. Siegel;J.K. Wolf

  • VLSI architectures for metric normalization in the Viterbi algorithm

    C.B. Shung;P.H. Siegel;G. Ungerboeck;H.K. Thapar

  • Turbo decoding for PR4: parallel versus serial concatenation

    T. Souvignier;A. Friedmann;M. Oberg;P.H. Siegel

  • Joint message-passing decoding of LDPC codes and partial-response channels

    B.M. Kurkoski;P.H. Siegel;J.K. Wolf

  • Lee-metric BCH codes and their application to constrained and partial-response channels

    R.M. Roth;P.H. Siegel

  • Adaptive Methods for Linear Programming Decoding

    M.-H.N. Taghavi;P.H. Siegel

  • Enhanced belief propagation decoding of polar codes through concatenation.

    Jing Guo;Minghai Qin;Albert Guillen i Fabregas;Paul H. Siegel

  • Error characterization and coding schemes for flash memories

    Eitan Yaakobi;Jing Ma;Laura Grupp;Paul H. Siegel

  • Windowed Decoding of Spatially Coupled Codes

    Aravind R. Iyengar;Paul H. Siegel;Rüdiger L. Urbanke;Jack Keil Wolf

  • Gaussian belief propagation solver for systems of linear equations

    O. Shental;P.H. Siegel;J.K. Wolf;D. Bickson

  • Coding Over Sets for DNA Storage

    Andreas Lenz;Paul H. Siegel;Antonia Wachter-Zeh;Eitan Yaakobi

  • Turbo decoding for partial response channels

    T.V. Souvignier;M. Oberg;P.H. Siegel;R.E. Swanson

  • WITT SPACES: A GEOMETRIC CYCLE THEORY FOR KO-HOMOLOGY

    At Odd Primes;Paul Howard Siegel

  • Finite fields for Computer Scientists and Engineers [Book Review]

    P.H. Siegel

Frequent Co-Authors

Jack K. Wolf
Jack K. Wolf University of California, San Diego
Eitan Yaakobi
Eitan Yaakobi Technion – Israel Institute of Technology
Alexander Vardy
Alexander Vardy University of California, San Diego
Ron M. Roth
Ron M. Roth Technion – Israel Institute of Technology
Henry D. Pfister
Henry D. Pfister Duke University
L.B. Milstein
L.B. Milstein University of California, San Diego
Jehoshua Bruck
Jehoshua Bruck California Institute of Technology
Steven Swanson
Steven Swanson University of California, San Diego
Danny Dolev
Danny Dolev Hebrew University of Jerusalem
Giovanni Emanuele Corazza
Giovanni Emanuele Corazza University of Bologna

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