Larissa T. Triess

Machine Learning | Autonomous Driving | Computer Vision


I use machine learning to make autonomous vehicles perceive and understand their environment.

I am a Machine Learning Engineer in the Scene Understanding Group at Mercedes-Benz R&D. I am technical lead of an international software development team for autonomous driving perception that works together with Nvidia to enable L3 high-speed driving on the highway.

At the same time, I am also lecturer at the University of Stuttgart where I am teaching the Master’s course “Advanced Visual Processing” at the department of Electrical Engineering.

Previously, I was a PhD student with the LiDAR Perception Group at Mercedes-Benz R&D and the Karlsruhe Institute of Technology (KIT), where I was advised by Prof. J. Marius Zöllner. My research is published under the title “LiDAR Domain Adaptation - Automotive 3D Scene Understanding”.


Apr 1, 2024 The new semester has started - now with me as a lecturer
Feb 14, 2024 I held a talk about building an end-to-end differentiable stack for automated driving at the Autonomous Driving Meetup in Stuttgart 🚀
Jan 30, 2024 I will serve as an associate editor as area chair for the workshops of this year’s IEEE Intelligent Vehicles Symposium.
Jan 24, 2024 I was approved to become a lecturer at the Department of Electrical Engineering at the University of Stuttgart 🚀
Jan 2, 2024 Over 100 citations! Within the last year, I reached the magic number of 100 citations on my papers.

selected publications

  1. A Realism Metric for Generated LiDAR Point Clouds
    Larissa T. Triess, Christoph B. RistDavid Peter, and 1 more author
    International Journal of Computer Vision (IJCV), 2022
  2. Point Cloud Generation with Continuous Conditioning
    Larissa T. Triess, Andre Bühler, David Peter, and 2 more authors
    In Conference on Artificial Intelligence and Statistics (AISTATS), 2022
  3. A Survey on Deep Domain Adaptation for LiDAR Perception
    Larissa T. Triess, Mariella DreissigChristoph B. Rist, and 1 more author
    In Proc. IEEE Intelligent Vehicles Symposium (IV) Workshops, 2021