Meal planning for iOS.
React Native application for meal planning, grocery lists, and food journaling, with persistent local state and optional AI meal generation.
Robotics & software engineer.
I develop vehicle-data pipelines and ADAS scenario retrieval at Audi. Previously at Akkodis, I worked on ROS 2 integration and reinforcement-learning simulation.
01 / SELECTED PROJECTS
Software, robotics, and automotive data.
React Native application for meal planning, grocery lists, and food journaling, with persistent local state and optional AI meal generation.
Questionnaire preparation with source references, revision history, and approval controls for commercial insurance renewals.
Benchmarked PPO, SAC and TD3 in Gazebo/PX4 SITL with trajectory logging and repeatable evaluation. PPO achieved 5.5 cm mean final horizontal error over 100 simulation episodes.
Vehicle telemetry pipelines, computer vision, and CLIP semantic search for retrieving and reconstructing real driving scenarios.
An interactive fleet-planning prototype with simulated demand and an optional PPO backend. First place at the PAVE Europe Next Gen Challenge in Brussels.
Real-time perception, motion planning, and sensor integration in C++ / ROS 2 on NVIDIA Jetson for an autonomous Formula Student racecar.
FURTHER PROJECTS
Connecting perception, object detection, and navigation for a physical service robot.
A decision-support prototype combining explainable AI, data pipelines, and dashboards for aviation.
A Pixhawk-based platform for hardware assembly, flight-controller integration and future policy testing.
Exploring accident scenarios through simulation, reconstruction, and immersive visualization.
A peer-tutoring platform connecting students at TH Ingolstadt.
THREE.JS / INTERACTIVE VISUALISATION
A Three.js illustration of a quadrotor approaching a moving platform. Pause the sequence, change the camera, or inspect a point on the timeline.
SCENARIO STATE
Illustrative trajectory. Recorded Gazebo runs and benchmark results are available in the research project.
Read the thesis ↗02 / EXPERIENCE
Vehicle-data processing and scenario retrieval for driver-assistance simulation.
Developed a Gazebo/PX4 SITL landing benchmark with ROS 2 integration, policy training, trajectory logging and standardized evaluation of PPO, SAC and TD3. Physical policy transfer remains future work.
ROS 2 service robot integration, C++ perception and sensor interfaces, Nav2 navigation, and CARLA simulation scenarios for automated driving evaluation.
Real-time motion planning, multi-sensor integration, and embedded C++ / ROS 2 software on NVIDIA Jetson for an autonomous racecar.
B.Eng. · Graduated 2026
UAV precision landing research
INGOLSTADT, DE
03 / BACKGROUND
I’m based in Ingolstadt, Germany, with a B.Eng. in Autonomous Vehicle Engineering from TH Ingolstadt. My experience includes automotive data processing at Audi, ROS 2 integration at Akkodis, and driverless software for Schanzer Racing.
I work primarily in C++, Python, and TypeScript. My independent projects include Nouri, a meal-planning app, and Scope, an insurance-renewal workflow.
TECHNOLOGIES
Software, simulation and hardware integration.
SQL · ROS 2 · Linux · Docker · Git
PPO · SAC · TD3 · CLIP · Computer vision
PX4 SITL · Digital twins
LiDAR · RealSense · GNSS · IMU
BRUSSELS / 2025
First place at the PAVE Europe Next Gen Challenge for work on autonomous mobility and public acceptance.
Recommendation from Prof. Dr.-Ing. Michael Mecking ↗