🔊 Zeynep Akata has joined relAI as a Fellow!.
About Professor Zeynep Akata
Zeynep Akata is a Liesel Beckmann Distinguished Professor of Computer Science at TUM and the Director of the Institute for Explainable Machine Learning at Helmholtz Munich.
Her research focuses on explainability-guided model adaptation, bias detection and mitigation, mechanistic interpretability, and continual learning—all of which are central challenges for reliable AI. Methodologically, her work spans representation learning, interpretability diagnostics, model consolidation, and evaluation under distribution shift 📈, with close connections to real-world applications in medical imaging and clinical decision support.
Contribution to relAI
As a relAI Fellow, she will contribute to the relAI Curriculum through lectures, mentoring students, supporting relAI events, and participating in strategic discussions on evaluation standards and benchmarks for reliable AI.
