Highlights:

Skills:Python, Pytorch, Project Management, Machine Learnig, Automotive Engineering, Deep Learning, Generative AI

Research Associate 05/2019 - current
RPTU Kaiserslautern-Landau, , Germany
Research Associate with 3+ years of hands-on experience in Machine Learning and 5+ years in project management, automotive testing and laboratory environments. Specialized in modeling physical systems with artificial intelligence based on self-developed test scenarios and experienced in generative AI. Strong research background and multiple publications at high quality international conferences (SAE, IEEE), currently finalizing the PhD thesis - creating unique hybrid ML-physical/phenomenological based models. Experienced in managing international industrial and publicly funded projects.
09/20-today: - Project lead in a publicly funded research project: Development of an operating strategy for hybrid vehicles optimized for minimum pollutant emissions based on a highly transient emission model and the use of AI methods. - Utilization of data-based and physical-phenomenological model approaches and their unification (grey box). - Extending the findings to general, efficient modeling of physical systems through the help of AI. - Setting up a local, finetuned LLM with RAG to enhance research 05/19-08/20: - Responsible for the planning and execution of the test series for the optimization of a CNG engine. Collaboration with an industrial customer, communication and presentation in an international project team.--

RPTU Kaiserslautern-Landau 05/2019 - current
Kaiserslautern, , Germany
Degree: Doctoral Degree
Major:Automotive Engineering
Minor:Machine Learning
Building novel hybrid ML/physical models to simulate the highly dynamic emission behaviour of combustion engines.

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