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Bernhard Jaeger
I am a PhD student at the University of Tübingen, where I am part of the Autonomous Vision Group led by Prof. Andreas Geiger. My research is supported by the International Max Plank Research School for Intelligent Systems.
Research:
My goal is to solve autonomous driving, which I view as an embodied intelligence problem.
My research has contributed to the development of end-to-end driving technology, which by now is being widely adopted by leading industry players like Waymo, Tesla, or NVIDIA.
I worked on the TransFuser series of models, which is a widely used baseline in the literature. Our survey, "End-to-end autonomous driving: Challenges and frontiers" is the most cited introductory text in the field of end-to-end driving.
Recently I have been working on reinforcement learning (RL) techniques for training planning policies.
Our method, CaRL is the first open-source RL policy that outperformed the leading imitation learning methods on the nuPlan benchmark.
I am committed to open contribution to the community. All my papers are freely available on arXiv, and all my code is available on GitHub.
Currently, I am building a non-profit research organization to solve and open-source the science behind level 5 driving. We will be raising money and hiring people. Email me if you are interested.
Bio: I studied B.Sc. Informatics: Games Engineering at the Technical University of Munich. Following that I worked for 1 year as a software developer at FERCHAU as graphics developer. Afterwards I did a M.Sc. in Computer Science at the University of Tübingen. I started my PhD at the Autonomous Vision Group in April 2022.
Publications
Long Nguyen, Micha Fauth, Bernhard Jaeger, Daniel Dauner, Maximilian Igl, Andreas Geiger, Kashyap Chitta
arXiv.org, 2025
Abs / Paper / Code /
@article{Nguyen2025ARXIV,
author = {Long Nguyen and Micha Fauth and Bernhard Jaeger and Daniel Dauner and Maximilian Igl and Andreas Geiger and Kashyap Chitta},
title = {LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving},
year = {2025},
journal = {arXiv.org},
}
Bernhard Jaeger, Daniel Dauner, Jens Beißwenger, Simon Gerstenecker, Kashyap Chitta, Andreas Geiger
Proc. of the Conf. on Robot Learning (CoRL), 2025
Abs / Paper / Code /
@InProceedings{Jaeger2025CoRL,
author = {Bernhard Jaeger and Daniel Dauner and Jens Beißwenger and Simon Gerstenecker and Kashyap Chitta and Andreas Geiger},
title = {CaRL: Learning Scalable Planning Policies with Simple Rewards},
booktitle = {Proc. of the Conf. on Robot Learning (CoRL)},
year = {2025},
}
Bernhard Jaeger, Andreas Geiger
Foundations and Trends® in Optimization, 2024
Abs / Paper /
@article{Jaeger2024FTO,
author = {Bernhard Jaeger and Andreas Geiger},
title = {An Invitation to Deep Reinforcement Learning},
year = {2024},
journal = {Foundations and Trends® in Optimization},
}
Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, Hongyang Li
Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2024
Abs / Paper / Code /
@article{Chen2024PAMI,
author = {Li Chen and Penghao Wu and Kashyap Chitta and Bernhard Jaeger and Andreas Geiger and Hongyang Li},
title = {End-to-end Autonomous Driving: Challenges and Frontiers},
year = {2024},
journal = {Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)},
}
Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
Proc. of the International Conf. on Learning Representations (ICLR), 2024
Abs / Paper / Code / Website /
@InProceedings{Miyato2024ICLR,
author = {Takeru Miyato and Bernhard Jaeger and Max Welling and Andreas Geiger},
title = {GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers},
booktitle = {Proc. of the International Conf. on Learning Representations (ICLR)},
year = {2024},
}
Bernhard Jaeger, Kashyap Chitta, Andreas Geiger
Proc. of the IEEE International Conf. on Computer Vision (ICCV), 2023
Abs / Paper / Video / Poster / Code /
@InProceedings{Jaeger2023ICCV,
author = {Bernhard Jaeger and Kashyap Chitta and Andreas Geiger},
title = {Hidden Biases of End-to-End Driving Models},
booktitle = {Proc. of the IEEE International Conf. on Computer Vision (ICCV)},
year = {2023},
}
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger
Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023
Abs / Paper / Supplemental / Video / Poster / Code /
@article{Chitta2023PAMI,
author = {Kashyap Chitta and Aditya Prakash and Bernhard Jaeger and Zehao Yu and Katrin Renz and Andreas Geiger},
title = {TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving},
year = {2023},
journal = {Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)},
}
Bernhard Jaeger
University of Tübingen, 2021
Paper /
@mastersthesis{Jaeger2021Thesis,
author = {Bernhard Jaeger},
title = {Expert Drivers for Autonomous Driving},
year = {2021},
school = {University of Tübingen},
}Talks
Machine Learning for Autonomous Driving Workshop - NeurIPS, 2022
Other activities
- One concern that I have as an AI researcher when publishing code is that it can potentially be used in dual-use applications. To solve this, I developed the Civil Software Licenses, which prevent dual-use of open-source software while being minimal in the restrictions they impose.
- I am a proponent of rigorous experimental evaluation in autonomous driving research and wrote a guide about common mistakes in the community to help people avoid common pitfalls.
- The TransFuser series of models is in version 6 already. I have created a history document for people to have an easier overview.
News
| Oct 26, 2026 | I was selected as Top Reviewer at NeurIPS 2025. |
| Jul 01, 2025 | The Vector Stiftung (foundation) supports my research with a grant of 91600 € for the project "Skalierung von verstärkendem Lernen für Ende-zu-Ende Methoden für autonomes Fahren". The grant was competitive, with a 5% acceptance rate (15/300). |
| Jun 11, 2025 | Our team placed 2nd in the Waymo Vision-based End-to-End Driving Challenge held at the CVPR 2025 Workshop on Autonomous Driving. |
| Jun 11, 2025 | Our team placed 3rd in the Scenario Generation Challenge held at the CVPR 2025 Workshop on Autonomous Driving. |
| Jun 17, 2024 | Our team placed 2nd in the CARLA Challenge held at the CVPR 2024 Workshop Foundation Models for Autonomous Systems |
| Dec 14, 2023 | Our team placed 2nd in the CARLA Sensor Track challenge held at the Machine Learning for Autonomous Driving Symposium in New Orleans. |
| Nov 21, 2022 | Our team won the CARLA leaderboard MAP Track challenge at the NeurIPS 2022 Machine Learning for Autonomous Driving workshop. |
| Apr 01, 2022 | I joined the University of Tübingen as a PhD student. |
| Nov 22, 2021 | Our team placed 2nd in the NeurIPS 2021 CARLA Machine Learning for Autonomous Driving autonomous driving challenge . |
Website template provided by Michael Niemeyer.
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