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.

Ansprechpartner

Interesse an dem Thema? Informieren Sie sich mit unseren Publikationen über unsere aktuelle Forschung.

Für mehr Informationen wenden Sie sich mit ihren Bewerbungsunterlagen bitte an Dr. rer. nat. Evgeny Kusmenko.

Aufgabenstellung:

Prof. Dr. Bernhard Rumpe
Lehrstuhl Software Engineering
Ahornstr. 55
52074 Aachen