Foto von Christian Creß

M.Sc. Christian Creß

Technische Universität München

Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)


Boltzmannstr. 3
85748 Garching b. München


Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)

Schleißheimerstraße 90a(8111)
85748 Garching b. München

Curriculum Vitae

Christian Creß joined the Chair of Robotics, Artificial Intelligence and Real-time Systems at the Technical University of Munich (TUM) in 2020 as Research Assistant and Ph.D. candidate under the supervison of Prof. Dr.-Ing. habil. Alois Christian Knoll. He completed his M.Sc. in Applied Computer Science at the University of Applied Sciences Kempten in 2016. His Master Thesis “Visual Scene Analysis for the Segmentation of Static and Dynamic Objects” was realized in collaboration with ESG Elektroniksystem- und Logistik-GmbH. Before starting as Research Assistant at TUM, he worked as software developer in the industry. 

At his current position, he is working in the Providentia++ project with the goal of creating a digital twin of the traffic on the freeway A9 and the highway B471 near Munich.

e-Mail: christian.cress [at]


Research Interests

  • Computer Vision
  • Artificial Intelligence
  • Augmented Reality
  • Software Architecture

Thesis Supervision

Open Thesis Topics:


Completed and Ongoing Theses:

Title Author Status Type
Accident Prevention Frontend Framework to Support Autonomous Driving Mohammad Naanaa Ongoing Bachelor Thesis
Accident Prevention Backend Framework to Support Autonomous Driving Noir Nigmatov Ongoing Master Thesis
Traffic Trajectory Prediction Within the Providentia++ Test Stretch Jurek Olden Ongoing Master Thesis
Enhancing Robustness of Intelligent Transportation Systems Through Self-Diagnosis Functionality Lukas Rabe Submitted 06/21 Master Thesis




  • Creß, Christian; Zimmer, Walter; Strand, Leah; Fortkord, Maximilian; Dai, Siyi; Lakshminarasimhan, Venkatnarayanan; Knoll, Alois: A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Research. 33rd IEEE Intelligent Vehicles Symposium (IV), 2022 mehr… BibTeX