People

• Efficient machine learning hardware-software architectures
• Hardware accelerators for AI algorithms and systems
• AI computing with emerging devices, e.g., RRAM (Resistive Random Access Memory) and optical components
• Circuit and system design methodologies for AI
• Explainability of AI
• Neuromorphic computing

Since 2022 Assistant Professor (Tenure Track) for Hardware for Artificial Intelligence, TU Darmstadt

2018-2022 Group Leader on Heterogeneous Computing, TU Munich

2014-2018 Dr.-Ing. in Electrical and Computer Engineering (summa cum laude), TU Munich