Bachelor-/Masterthesis Themen: Artificial Intelligence for Automotive and Embedded Systems
DEEP LEARNING
Design, model, train and validate deep neural networks as components for embedded systems or in the automotive domain.
MODELING
Model Software- and Systems Architecture components with neural network functionality on different level of abstraction for cyber-physical systems and cars. Implement code generation mechanisms based on your model.
DATA MANAGEMENT
Cope with huge datasets and the complexity of storing them efficiently, as well as handling different data versions and searching for errors.
AUTOMOTIVE
Work in projects in the automotive domain and apply different AI-technologies on multifaceted problems all around the engineering process of a modern car.
SIMULATION
Develop and test simulation environments to then apply them to problems in the cyber-physical systems domain.
MLOps
Simplify the complete life cycle of Machine Learning solutions by automating steps and offering infrastructure for different parties.
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Aufgabenstellung:
Prof. Dr. Bernhard Rumpe
Lehrstuhl Software Engineering
Ahornstr. 55
52074 Aachen