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.
[3] Akata's research interests focus on Explainable Multimodal Machine Learning which is in the intersection between Machine Learning, Computer Vision and Natural Language Processing.