Feedback Optimization

Feedback Optimization is a methodological framework within adaptive feedback systems that systematically enhances feedback quality and delivery by dynamically adjusting feedback parameters based on learner performance, engagement, and contextual data to maximize learning outcomes.

71

Publications

2.9K

Citations

222

Authors

95

Institutions

Publications per year

2017–2026

28

Authors

222

  1. SB
    Saverio Bolognani

    ETH Zurich, Switzerland

    6 publications · 223 citations

    6

    h-index

  2. FD
    Florian Dörfler

    ETH Zurich, Switzerland

    6 publications · 216 citations

    6

    h-index

  3. LO
    Lukas Ortmann

    ETH Zurich, Switzerland

    5 publications · 192 citations

    5

    h-index

  4. NL
    Na Li

    Harvard University, United States

    2 publications · 37 citations

    2

    h-index

  5. AH
    Adrian Hauswirth

    ETH Zurich, Switzerland

    2 publications · 108 citations

    2

    h-index

1–5 of 222

Venues

  1. Optics Express

    6 publications · 116 citations

    6

    h-index

  2. IEEE Transactions on Automatic Control

    4 publications · 125 citations

    3

    h-index

  3. Electric Power Systems Research

    2 publications · 108 citations

    2

    h-index

  4. Nonlinear Dynamics

    2 publications · 55 citations

    2

    h-index

  5. Biotechnology and Bioengineering

    2 publications · 103 citations

    2

    h-index

1–5