| Nationality: | Turkish |
| Workplaces: | University of Tübingen |
| Alma Mater: | INRIA Grenoble-Rhônes-Alpes (PhD) |
| Thesis Title: | Contributions to large-scale learning for image classification |
| Thesis Url: | https://lear.inrialpes.fr/people/akata/Zeynep_Akata_PhD |
| Thesis1 Url: | and |
| Thesis2 Url: | )--> |
| Thesis Year: | 2014 |
| Doctoral Advisor: | Cordelia Schmid |
| Spouses: | )--> |
| Partners: | )--> |
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]
Akata received her undergraduate degree in Trakya University[3] in Turkey 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 before joining the University of Tübingen in 2019.
Akata's research interests focus on explainable machine learning, multi-modal learning, and low-shot learning.[4] [5]