| Titel | BA | SA | MA | HW | exp | the | kon | Eintrag |
|---|---|---|---|---|---|---|---|---|
| Rate my driving: Developing an AI Framework for the Multi-Dimensional Assessment of Human-Likeness in Driving Behavior | 2026-03-02 |
| christian.oefinger@tum.de | |
| Phone | +49 89 289 10446 |
| Room number | Hochbrück 3.4.21 |
| ORCID | ORCID |
| Google Scholar | Google Scholar Profile |
| Researchgate | Researchgate Profile |
Research Topics
- Autonomous Vehicles
- Autoware
- Performance Assessment and Benchmarking of Software Stacks for Autonomous Driving
Vita
I earned my bachelor’s degree in mechanical engineering from the Technical University of Munich (TUM) in 2022, where I developed a strong interest in electromobility. During this time, I gained hands-on experience through an internship at BMW Group, working on the development of high-voltage battery systems. For my bachelor’s thesis at the Chair of Automotive Technology (FTM), I focused on creating precise 3D models of large-format lithium-ion battery cells.
Building on this foundation, I completed my master’s degree in automotive engineering at TUM in 2025. Throughout my master’s studies, I deepened my expertise in battery technologies and discovered my passion for autonomous driving. As part of a semester project at FTM, I developed an AI-based digital twin approach for predictive maintenance of battery packs. My master’s thesis explored the strengths and limitations of modular versus end-to-end approaches for autonomous driving, which involved integrating components of the Autoware Universe software stack into a simulation environment and benchmarking them against a state-of-the-art end-to-end model in safety-critical scenarios.
Since December 2025, I have been pursuing my doctoral studies at the Chair of Autonomous Vehicle Systems (AVS) at TUM under the supervision of Prof. Dr.-Ing. Johannes Betz. My current research focuses on evaluating and benchmarking software stacks for autonomous driving.