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Michael Mitzenmacher

Michael Mitzenmacher

D-Index & Metrics

Computer Science

D-Index
91
Citations
50480
World Ranking
563
National Ranking
299

Research.com Recognitions

  • 2014 - ACM Fellow For contributions to coding theory, hashing algorithms and data structures, and networking algorithms.
  • 2000 - Fellow of Alfred P. Sloan Foundation

Overview

Michael Mitzenmacher is affiliated with Harvard University in the United States. Their primary research area is computer science, with a focus on several subfields including computer networks and communications, artificial intelligence, computer vision and pattern recognition, electrical and electronic engineering, and computational theory and mathematics.

They have contributed to a wide range of research topics, notably:

  • Caching and Content Delivery
  • Optimization and Search Problems
  • Advanced Queuing Theory Analysis
  • Algorithms and Data Compression
  • Software-Defined Networks and 5G
  • Sparse and Compressive Sensing Techniques
  • Machine Learning and Algorithms

Mitzenmacher's recent publications include the following papers:

  • Algorithms with predictions, 2022, Communications of the ACM
  • Adaptive Cuckoo Filters, 2020, ACM Journal of Experimental Algorithmics
  • Scheduling with Predictions and the Price of Misprediction, 2020, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

These publications demonstrate a focus on algorithm design and network-related algorithms. Additionally, Mitzenmacher has been associated with papers authored by frequent collaborators, reinforcing a network of research in related domains.

Frequent co-authors include:

  • Ran Ben Basat
  • Shay Vargaftik
  • Minlan Yu
  • Rana Shahout
  • Charalampos E. Tsourakakis

Mitzenmacher has published in various venues that are central to computer science research, such as:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the VLDB Endowment
  • Internet Mathematics

Professional recognition includes being named an ACM Fellow in 2014 for contributions to coding theory, hashing algorithms and data structures, and networking algorithms. Earlier in their career, Mitzenmacher was also recognized as a Fellow of the Alfred P. Sloan Foundation in 2000.

Best Publications

  • Detecting Novel Associations in Large Data Sets

    David N. Reshef;David N. Reshef;David N. Reshef;Yakir A. Reshef;Yakir A. Reshef;Hilary K. Finucane;Sharon R. Grossman;Sharon R. Grossman

  • Probability and Computing: Randomized Algorithms and Probabilistic Analysis

    Michael Mitzenmacher;Eli Upfal

  • Network Applications of Bloom Filters: A Survey

    Andrei Z. Broder;Michael Mitzenmacher

  • A Brief History of Generative Models for Power Law and Lognormal Distributions

    Michael D. Mitzenmacher

  • A digital fountain approach to reliable distribution of bulk data

    John W. Byers;Michael Luby;Michael Mitzenmacher;Ashutosh Rege

  • The power of two choices in randomized load balancing

    M. Mitzenmacher

  • Privacy preserving keyword searches on remote encrypted data

    Yan-Cheng Chang;Michael Mitzenmacher

  • Min-Wise Independent Permutations

    Andrei Z Broder;Moses Charikar;Alan M Frieze;Michael Mitzenmacher

  • Efficient erasure correcting codes

    M.G. Luby;M. Mitzenmacher;M.A. Shokrollahi;D.A. Spielman

  • Improved low-density parity-check codes using irregular graphs

    M.G. Luby;M. Mitzenmacher;M.A. Shokrollahi;D.A. Spielman

  • Compressed Bloom filters

    Michael Mitzenmacher

  • Practical loss-resilient codes

    Michael G. Luby;Michael Mitzenmacher;M. Amin Shokrollahi;Daniel A. Spielman

  • Probability and computing

    Michael Mitzenmacher

  • Cuckoo Filter: Practically Better Than Bloom

    Bin Fan;Dave G. Andersen;Michael Kaminsky;Michael D. Mitzenmacher

  • Less hashing, same performance: Building a better Bloom filter

    Adam Kirsch;Michael Mitzenmacher

  • A digital fountain approach to asynchronous reliable multicast

    J.W. Byers;M. Luby;M. Mitzenmacher

  • The Power of Two Random Choices: A Survey of Techniques and Results

    Michael Mitzenmacher;Andrea W. Richa;Ramesh Sitaraman

  • An improved construction for counting bloom filters

    Flavio Bonomi;Michael Mitzenmacher;Rina Panigrahy;Sushil Singh

  • Analysis of low density codes and improved designs using irregular graphs

    M. Luby;M. Mitzenmacher;A. Shokrollah;D. Spielman

  • Min-wise independent permutations (extended abstract)

    Andrei Z. Broder;Moses Charikar;Alan M. Frieze;Michael Mitzenmacher

  • Improved low-density parity-check codes using irregular graphs and belief propagation

    M.G. Luby;M. Amin Shokrolloahi;M. Mizenmacher;D.A. Spielman

  • Probability and computing : an introduction to randomizedalgorithms and probabilistic analysis

    Michael Mitzenmacher;Eli Upfal

Frequent Co-Authors

Michael T. Goodrich
Michael T. Goodrich University of California, Irvine
John W. Byers
John W. Byers Boston University
Michael Luby
Michael Luby BitRipple
Andrei Z. Broder
Andrei Z. Broder Google (United States)
Eli Upfal
Eli Upfal Brown University
Pardis C. Sabeti
Pardis C. Sabeti Harvard University
Georgios Zervas
Georgios Zervas University College London
Roberto Tamassia
Roberto Tamassia Brown University
George Varghese
George Varghese University of California, Los Angeles
Susanne Albers
Susanne Albers Technical University of Munich

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