World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6045
World Ranking
8933
National Ranking
3802

Overview

Michael Langberg is affiliated with the University at Buffalo, State University of New York in the United States. Their research primarily spans the fields of computer science and engineering, with a focus on areas such as computer networks and communications, electrical and electronic engineering, and artificial intelligence.

Their scholarly contributions include 42 publications in computer science and 25 in engineering. Notable subfields covered by their work include computer networks and communications (25 publications), electrical and electronic engineering (21 publications), artificial intelligence (8 publications), molecular biology (6 publications), and computational theory and mathematics (5 publications).

Langberg's research topics tend to cluster around cooperative communication and network coding, wireless communication security techniques, error correcting code techniques, DNA and biological computing, coding theory and cryptography, cellular automata and applications, and SARS-CoV-2 detection and testing.

Frequent coauthors in their work include Michelle Effros, Mira Gonen, Alex Sprintson, Oliver Kosut, and Yihan Zhang. This collaborative network reflects ongoing engagement with peers active in information theory and communications research.

Their publications have appeared in several venues, with significant representation in arXiv (Cornell University) for preprints, IEEE Transactions on Information Theory, the 2022 IEEE International Symposium on Information Theory (ISIT), IEEE Transactions on Signal Processing, and Foundations and Trends® in Communications and Information Theory.

Recent selected publications of Michael Langberg include:

  • Network Coding Multicast Key-Capacity, 2022, 2022 IEEE Information Theory Workshop (ITW)
  • Codes for Adversaries: Between Worst-Case and Average-Case Jamming, 2024, Foundations and Trends® in Communications and Information Theory
  • Group Testing on General Set-Systems, 2022, 2022 IEEE International Symposium on Information Theory (ISIT)
  • The Capacity of Causal Adversarial Channels, 2022, 2022 IEEE International Symposium on Information Theory (ISIT)
  • Reduced-Rank L1-Norm Principal-Component Analysis With Performance Guarantees, 2020, IEEE Transactions on Signal Processing

Best Publications

  • Resilient network coding in the presence of Byzantine adversaries

    S. Jaggi;M. Langberg;S. Katti;T. Ho

  • A unified framework for approximating and clustering data

    Dan Feldman;Michael Langberg

  • Resilient Network Coding in the Presence of Byzantine Adversaries

    S. Jaggi;M. Langberg;S. Katti;T. Ho

  • The encoding complexity of network coding

    M. Langberg;A. Sprintson;J. Bruck

  • Approximation Algorithms for Maximization Problems Arising in Graph Partitioning

    Uriel Feige;Michael Langberg

  • The encoding complexity of network coding

    Michael Langberg;Alexander Sprintson;Jehoshua Bruck

  • Realtime classification for encrypted traffic

    Roni Bar Yanai;Michael Langberg;David Peleg;Liam Roditty

  • An Equivalence Between Network Coding and Index Coding

    Michelle Effros;Salim El Rouayheb;Michael Langberg

  • On the Hardness of Approximating the Network Coding Capacity

    Michael Langberg;Alex Sprintson

  • Universal ε-approximators for integrals

    Michael Langberg;Leonard J. Schulman

  • Local graph coloring and index coding

    Karthikeyan Shanmugam;Alexandros G. Dimakis;Michael Langberg

  • Fault Tolerant Spanners for General Graphs

    S. Chechik;M. Langberg;D. Peleg;L. Roditty

  • The RPR 2 rounding technique for semidefinite programs

    Uriel Feige;Michael Langberg

  • On the hardness of approximating the network coding capacity

    M. Langberg;A. Sprintson

  • Correction of adversarial errors in networks

    S. Jaggi;M. Langberg;T. Ho;M. Effros

  • Communicating the Sum of Sources Over a Network

    A. Ramamoorthy;M. Langberg

  • Private codes or succinct random codes that are (almost) perfect

    M. Langberg

  • On the complementary Index Coding problem

    M. A. R. Chaudhry;Z. Asad;A. Sprintson;M. Langberg

  • On the fundamental limits of caching in combination networks

    Mingyue Ji;Ming Fai Wong;Antonia M. Tulino;Jaime Llorca

  • Improved Approximation of MAX-CUT on Graphs of Bounded Degree

    Uriel Feige;Marek Karpinski;Michael Langberg

  • An equivalence between network coding and index coding

    M. Effros;S. El Rouayheb;M. Langberg

  • The RPR2 Rounding Technique for Semidefinite Programs

    Uriel Feige;Michael Langberg

Frequent Co-Authors

Michelle Effros
Michelle Effros California Institute of Technology
Jehoshua Bruck
Jehoshua Bruck California Institute of Technology
Alex Sprintson
Alex Sprintson Texas A&M University
Tracey Ho
Tracey Ho California Institute of Technology
Uriel Feige
Uriel Feige Weizmann Institute of Science
Leonard J. Schulman
Leonard J. Schulman California Institute of Technology
Eitan Yaakobi
Eitan Yaakobi Technion – Israel Institute of Technology
David Peleg
David Peleg Weizmann Institute of Science
Liam Roditty
Liam Roditty Bar-Ilan University
Atri Rudra
Atri Rudra University at Buffalo, State University of New York

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