Automated Feature Engineering

Automated Feature Engineering is an academic method within the domain of feature construction that systematically generates domain-specific features from raw data through algorithmic means, distinguishing itself from manual feature design by enabling scalable, reproducible, and context-adaptive feature discovery without relying on extensive human intervention.

210

Publications

13.6K

Citations

776

Authors

343

Institutions

Publications per year

2017–2026

126

Authors

776

  1. DB
    David Benavides

    Universidad de Sevilla, Spain

    7 publications · 536 citations

    7

    h-index

  2. UK
    Udayan Khurana

    IBM (United States), United States

    6 publications · 690 citations

    6

    h-index

  3. HS
    Horst Samulowitz

    IBM (United States), United States

    6 publications · 690 citations

    6

    h-index

  4. AR
    Antonio Ruiz–Cortés

    Universidad de Sevilla, Spain

    5 publications · 457 citations

    5

    h-index

  5. DS
    Deepak S. Turaga

    IBM Research - Thomas J. Watson Research Center, United States

    4 publications · 654 citations

    4

    h-index

1–5 of 776

Venues

  1. IEEE Access

    10 publications · 767 citations

    10

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 536 citations

    8

    h-index

  3. IEEE Transactions on Software Engineering

    TSE · 3 publications · 173 citations

    3

    h-index

  4. PLoS ONE

    3 publications · 552 citations

    3

    h-index

  5. Information and Software Technology

    2 publications · 101 citations

    2

    h-index

1–5