Joachim Baumann

Arbeit an der ZHAW

Tätigkeit an der ZHAW

Doktorand in Algorithmic Fairness

fair-ai.ch

Aus- und Weiterbildung

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

algorithmic fairness, data science for social good

Beruflicher Werdegang

2022: Data Science for Social Good / Data Science Fellow / Carnegie Mellon University
2019-2020: Research Assistant / Teaching Assistant / Tutor, University of Zurich
2018-2019: Management- and Technology Consultant, Campana & Schott Switzerland AG
2014-2015: Internship Application Development, Lifeware SA Zürich

Aus- und Fortbildung

MSc in Informatics, 2021, Universität Zürich
BSc in Informatics, 2019, Universität Zürich

Mitglied in Netzwerken

• Digital Society Initiative
• PhD Programme in Data Science
• MD4SG
• Data Ethics Expert Group
• PhD students in AI Ethics

Projekte

• Algorithmic Fairness in data-based decision making: Combining ethics and technology / Teammitglied / Projekt abgeschlossen

Publikationen

• Baumann, Joachim; Hannák, Anikó; Heitz, Christoph,

  2022.

  Enforcing group fairness in algorithmic decision making : utility maximization under sufficiency [Paper].

  In:

  Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency.

  5th ACM Conference on Fairness, Accountability, and Transparency (FAccT), Seoul, Republic of Korea, 21-24 June 2022.

  New York:

  Association for Computing Machinery.

  S. 2315-2326.

  Verfügbar unter: https://doi.org/10.1145/3531146.3534645

• Baumann, Joachim; Heitz, Christoph,

  2022.

  Group fairness in prediction-based decision making : from moral assessment to implementation [Paper].

  In:

  Proceedings 2022 9th Swiss Conference on Data Science (SDS).

  9th Swiss Conference on Data Science (SDS), Lucerne, Switzerland, 22-23 June 2022.

  IEEE.

  S. 19-25.

  Verfügbar unter: https://doi.org/10.1109/SDS54800.2022.00011

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