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's research interests focus on Explainable Multimodal Machine Learning which is in the intersection between Machine Learning, Computer Vision and Natural Language Processing. Below are some of the subfields that she has been actively working on:
- Zero-Shot Learning and Few Shot Learning
- Weakly Supervised Learning
- Generative modeling with multimodal large language models and large language models: data augmentation via GANs, VAEs, SD
- Audio-visual learning, event detection
- Explainability: Transparency, Robustness, Bias mitigation in multimodal large language models