Natalie Maman

Natalie Maman, M.Sc., is a Researcher at the Intelligent Embedded Systems department within the Faculty of Computer Science at the University of Duisburg-Essen since October 2024. She holds a Bachelor's degree in Applied Computer Science (2019) with a focus on Engineering Informatics and a Master's degree in Computer Science (2023) specializing in Distributed Dependable Systems. Her academic journey included a year as an Application Software Engineer in industry before returning to academia.

• Education: B.Sc. Applied Computer Science (2019, UDE), M.Sc. Computer Science (2023, UDE)
• Current Role: Researcher, Intelligent Embedded Systems (since Oct 2024)

Her research focuses on adaptive embedded systems and machine learning, particularly addressing data drift compensation through autoencoder retraining in neural spike sorting. Current work centers on the TransfAIr project, which develops transfer learning methodologies for industrial AI applications and hardware-agnostic neural network deployment.

Recent publications emphasize hardware-aware neural architecture search techniques with mixed-precision quantization strategies. Her work bridges theoretical AI research with practical implementation challenges in embedded environments.