Algorithmic Matching

Algorithmic Matching is a computational method within multi-sided market design that systematically pairs participants or resources across interdependent sides according to predefined rules or optimization criteria to achieve desired market outcomes.

108

Publications

8.5K

Citations

279

Authors

160

Institutions

Publications per year

2017–2026

51

Authors

279

  1. IA
    Itai Ashlagi

    Stanford University, United States

    4 publications · 71 citations

    4

    h-index

  2. DS
    Daniela Sabán

    Columbia University, United States

    4 publications · 105 citations

    4

    h-index

  3. AM
    Aranyak Mehta

    Google (United States), United States

    4 publications · 960 citations

    4

    h-index

  4. AS
    Amin Saberi

    Stanford University, United States

    4 publications · 922 citations

    4

    h-index

  5. IA
    Itai Ashlagi

    Stanford University, United States

    3 publications · 137 citations

    3

    h-index

1–5 of 279

Venues

  1. SSRN Electronic Journal

    Repository · 6 publications · 78 citations

    6

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 121 citations

    3

    h-index

  3. JAMA

    2 publications · 121 citations

    2

    h-index

  4. PLoS ONE

    2 publications · 47 citations

    2

    h-index

  5. Operations Research

    2 publications · 118 citations

    2

    h-index

1–5