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M.Eng. Adam Theo Müller

M.Eng. Adam Theo Müller

Research Machine Learning in Autonomous Systems
Phone: +49 7131 504 6728
E-Mail: adam-theo.mueller@hs-heilbronn.de
Office address: G117
Postal address: Max-Planck-Str. 39, 74081

Research

Areas:

  • Autonomous Systems (perception, sensor fusion)
  • Machine Vision (machine learning in perception)
  • Cognitive Robotics


Publications:

PixCOIN, training and inference, results and extension
  • Adam T. Müller, Philipp J. Teuffel, Konstantin Manassis, and Nicolaj C. Stache, "Reducing Experimental Testing in Space Propulsion Film Cooling Analyses by Pixelwise Generative Image Interpolation," in 11th European Conference for Aeronautics and Aerospace Sciences (EUCASS), 2025
Robotic sorting Setup
  • Adam T. Müller, and Nicolaj C. Stache, "Visual Instruction as an Intuitive Interface for Robotic Sorting," in Artificial Intelligence in HCI: 6th International Conference (AI-HCII), 178-194, 2025, doi: 10.1007/978-3-031-93429-2_12
Faster FE calibration example results
  • Christoph David, Adam T. Müller, Moritz Kratt, and Sebastian Vohrer, "Test setup investigations for faster FE-calibration via advanced measurement techniques," in SAMPE Europe Conference, 2022, https://elib.dlr.de/192757/

I am interested in different use cases of machine learning and computer vision. My main research is in the field of Embodied AI. I am involved in the development of machine learning approaches for autonomous systems, mobile robots and cobots.

Before working at Heilbronn University, I had the opportunity to gain experience in various companies and research institutions in the fields of mechatronics, aerospace engineering and machine learning.

Image of a VW Passat autonomous vehicle

I supervise student theses in the subject areas of my research specialisations. You can view possible theses on the ZML website. More current topics can also be requested directly by e-mail to me.

You are welcome to submit your own ideas, but please base your proposal on the advertised topics. The decision as to whether a topic fits in with current research projects/areas of interest may result in us rejecting your proposals.

Requirements
Supervised Projects
  • Uncertainty Estimation in Machine Learning for Perception Tasks in Autonomous Driving (T. Rögelein)
  • Anonymization of Image Data for Autonomous Driving (D. Hägele, N. Richter)
  • Machine Learning enabled IMU Dead Reckoning (M. Rust)
  • Creation of a ROS2-based 1:8 traffic light system based on SUMO (D. Friedle, E. Schwarz, F. Weiß, E. Herzfeldt)
  • Autonomous 1:8-Car ROS2 integration and Depth-Camera Sensor Fusion for Obstacle Detection (L. Gerstlauer)
  • Cobot ROS2 integration and diffusion based sequential motion planning (J. Kurz, R. Walz)
  • Integration and VR visualisation of a multi-sensor perception module with Autoware (H. Erlewein)
  • Creation of a digital twin for the TechCampus of Heilbronn University in AWSIM (L. Scholl)
  • Creation of Colored Point Cloud Maps and 3D Meshes in Blender and Unity (J. Bany)
  • Integration of Vehicle and Sensor Models in Autoware Core / Universe (P. Lösch)
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