World's Best Scientists 2026 revealed!

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Computer Science

D-Index
68
Citations
25238
World Ranking
2043
National Ranking
1033

Research.com Recognitions

  • 2020 - ACM Fellow For design of efficient algorithmic techniques for big data, hashing, approximation algorithms, and metric embeddings
  • 2012 - ACM Paris Kanellakis Theory and Practice Award With Andrei Broder and Piotr Indyk, for their groundbreaking work on Locality-Sensitive Hashing that has had great impact in many fields of computer science including computer vision, databases, information retrieval, machine learning, and signal processing.
  • 2003 - Fellow of Alfred P. Sloan Foundation

Overview

Moses Charikar is affiliated with Stanford University in the United States. Their research spans primarily across computer science, with a focus on several subfields including artificial intelligence, computational theory and mathematics, statistics and probability, computer networks and communications, and signal processing.

Their work covers a variety of main topics, notably:

  • Complexity and Algorithms in Graphs
  • Algorithms and Data Compression
  • Game Theory and Voting Systems
  • Machine Learning and Algorithms
  • Data Management and Algorithms
  • Optimization and Search Problems
  • Markov Chains and Monte Carlo Methods

Moses Charikar has published extensively, with a significant number of papers appearing in venues such as arXiv (Cornell University), Leibniz-Zentrum für Informatik (Schloss Dagstuhl), Proceedings of the National Academy of Sciences, the IEEE Symposium on Foundations of Computer Science (FOCS), and the Proceedings of the VLDB Endowment.

Some recent papers include:

  • Distributed algorithms from arboreal ants for the shortest path problem, 2023, Proceedings of the National Academy of Sciences
  • Almost 3-Approximate Correlation Clustering in Constant Rounds, 2022, 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)
  • CoopStore, 2020, Proceedings of the VLDB Endowment
  • Near-Optimal Explainable k-Means for All Dimensions, 2021, arXiv (Cornell University)
  • The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood, 2020, arXiv (Cornell University)

Frequent co-authors include Kirankumar Shiragur, Prasanna Ramakrishnan, Erik Waingarten, Chirag Pabbaraju, and Kangning Wang.

Regarding awards, Moses Charikar has received several recognitions including the ACM Fellowship in 2020 for contributions to efficient algorithmic techniques for big data, hashing, approximation algorithms, and metric embeddings. In 2012, they were awarded the ACM Paris Kanellakis Theory and Practice Award alongside Andrei Broder and Piotr Indyk for their work on Locality-Sensitive Hashing. Earlier, they were also named a Fellow of the Alfred P. Sloan Foundation in 2003.

Best Publications

  • Similarity estimation techniques from rounding algorithms

    Moses S. Charikar

  • Min-Wise Independent Permutations

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

  • Finding Frequent Items in Data Streams

    Moses Charikar;Kevin Chen;Martin Farach-Colton

  • Incremental Clustering and Dynamic Information Retrieval

    Moses Charikar;Chandra Chekuri;Tomas Feder;Rajeev Motwani

  • Aggregating inconsistent information: Ranking and clustering

    Nir Ailon;Moses Charikar;Alantha Newman

  • Multi-probe LSH: efficient indexing for high-dimensional similarity search

    Qin Lv;William Josephson;Zhe Wang;Moses Charikar

  • Approximation Algorithms for Directed Steiner Problems

    Moses Charikar;Chandra Chekuri;To-yat Cheung;Zuo Dai

  • A constant-factor approximation algorithm for the k -median problem

    Moses Charikar;Sudipto Guha;Éva Tardos;David B. Shmoys

  • Efficient k-nearest neighbor graph construction for generic similarity measures

    Wei Dong;Charikar Moses;Kai Li

  • Clustering with qualitative information

    Moses Charikar;Venkatesan Guruswami;Anthony Wirth

  • Greedy approximation algorithms for finding dense components in a graph

    Moses Charikar

  • Improved combinatorial algorithms for the facility location and k-median problems

    M. Charikar;S. Guha

  • Min-wise independent permutations (extended abstract)

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

  • Algorithms for facility location problems with outliers

    Moses Charikar;Samir Khuller;David M. Mount;Giri Narasimhan

  • The smallest grammar problem

    M. Charikar;E. Lehman;Ding Liu;R. Panigrahy

  • Detecting high log-densities: an O(n¼) approximation for densest k-subgraph

    Aditya Bhaskara;Moses Charikar;Eden Chlamtac;Uriel Feige

  • Better streaming algorithms for clustering problems

    Moses Charikar;Liadan O'Callaghan;Rina Panigrahy

  • A constant-factor approximation algorithm for the k-median problem (extended abstract)

    Moses Charikar;Sudipto Guha;Éva Tardos;David B. Shmoys

  • Towards estimation error guarantees for distinct values

    Moses Charikar;Surajit Chaudhuri;Rajeev Motwani;Vivek Narasayya

  • Learning from untrusted data

    Moses Charikar;Jacob Steinhardt;Gregory Valiant

Frequent Co-Authors

Kai Li
Kai Li Princeton University
Venkatesan Guruswami
Venkatesan Guruswami University of California, Berkeley
Qin Lv
Qin Lv University of Colorado Boulder
Amit Sahai
Amit Sahai University of California, Los Angeles
Sudipto Guha
Sudipto Guha University of Pennsylvania
Chandra Chekuri
Chandra Chekuri University of Illinois at Urbana-Champaign
Michael Mitzenmacher
Michael Mitzenmacher Harvard University
Rajeev Motwani
Rajeev Motwani Stanford University
Rina Panigrahy
Rina Panigrahy Google (United States)
Aaron Sidford
Aaron Sidford Stanford University

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