Zeynep Akata

Zeynep Akata is a professor of computer science at the University of Tübingen[1] where she leads the Explainable Machine Learning group. Akata is also a Senior Research Scientist at the Max Planck Institute for Intelligent Systems, Tübingen.[2]

Zeynep Akata
Alma materINRIA Grenoble-Rhônes-Alpes (PhD)
Scientific career
InstitutionsUniversity of Tübingen
ThesisContributions to large-scale learning for image classification (2014)
Doctoral advisorCordelia Schmid
Websitewww.eml-unitue.de/people/zeynep-akata

Education and career

Akata received her Ph.D. in computer science at the INRIA Grenoble-Rhônes-Alpes. She was a post-doctoral research fellow at the Max Planck Institute for Informatics with Bernt Schiele and at University of California, Berkeley with Trevor Darrell. Akata was an assistant professor at the University of Amsterdam from 2017 to 2019 before joining the University of Tübingen in 2019.

Research

Akata's research interests focus on explainable machine learning, multi-modal learning, and low-shot learning.[3][4]

Selected awards and honours
  • 2021 German Pattern Recognition Award[5]
  • 2019 ERC Starting Grant[6][7]
  • 2019 Young Scientist Honour from the Werner-von-Siemens-Ring foundation[8]
  • 2014 Lise-Meitner Award for Excellent Women in Computer Science from the Max Planck Society[9]

References
  1. "Department of Computer Science, Tübingen". Retrieved 29 April 2022.
  2. "Max-Planck Institute for Intelligent Systems - Zeynep Akata". Retrieved 29 April 2022.
  3. "Website Zeynep Akata". Retrieved 29 April 2022.
  4. "Blog news article". 6 December 2021. Retrieved 2 May 2022.
  5. "Award winners German Pattern Recognition Award". Retrieved 2 May 2022.
  6. "ERC Grants 2019" (PDF). Retrieved 29 April 2022.
  7. "News ERC Grant awarded to Zeynep Akata". Retrieved 29 April 2022.
  8. "Young Scientist Honour from the Werner-von-Siemens-Ring foundation". 24 October 2017. Retrieved 29 April 2022.
  9. "Lise-Meitner Award". Retrieved 29 April 2022.
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