Perception
Radar and LiDAR processing, BEV prediction, scene flow, and computer vision.
I’m a robotics software and perception engineer based in Erlangen, Germany. My work combines radar and LiDAR perception, ROS-based robotics, and embedded deployment for autonomous systems. Alongside that I’m working toward connected and cooperative autonomy: teleoperation, trajectory and motion planning, CAVs and V2X.
My recent experience spans robotics software, systems integration, and perception engineering. At Valeo, that progression included Droid-side ROS and Jetson work, teleoperation integration, and a master’s thesis on motion-aware radar perception.
My academic foundation is an M.Sc. in Electromobility with a focus on AI and autonomous driving, built on an earlier mechanical-engineering background.
With appreciation for the engineering and research teams at Valeo whose collaboration supported and shaped this work.
Case studies here are presented using public datasets — nuScenes, Waymo, the Stanford Bunny — unless stated otherwise. Internal data and measurements are not published.
The portfolio is organized around the work I can demonstrate directly.
Radar and LiDAR processing, BEV prediction, scene flow, and computer vision.
ROS/ROS2, embedded Linux, NVIDIA Jetson, video streaming, and system integration.
Reproducible evaluation, technical documentation, and evidence-led decisions.
Hardware–software bring-up, embedded deployment, and debugging across the sensor–compute–actuator boundary.
Trajectory and motion planning, CAVs, V2X and cooperative robotic systems. Currently self-directed study rather than delivered work.