Zeynep Akata
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Zeynep Akata | |
|---|---|
| Alma mater | INRIA Grenoble-Rhônes-Alpes (PhD) |
| Scientific career | |
| Institutions | Technical University of Munich |
| Thesis | Contributions to large-scale learning for image classification (2014) |
| Doctoral advisor | Cordelia Schmid |
| Website | www |
Zeynep Akata is a Liesel Beckmann Distinguished professor of computer science at the Technical University of Munich[1] where she leads the Interpretable and Reliable Machine Learning chair. Akata is also the director of the Helmholtz Institute for Explainable Machine Learning.
Akata received her undergraduate degree in Trakya University[2] in Turkey, her MSc from RWTH Aachen and 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 and she was a full professor at the Cluster of Excellence Machine Learning at the University of Tübingen between 2019 and 2023. While in Tübingen, Akata was also a senior research scientist at the Max Planck Institute for Intelligent Systems, Tübingen.[3]
