🚀 Bridging the gap between precision manufacturing and Physical AI.
Welcome. I am a Robotics AI Researcher specializing in contact-aware robot learning, imitation learning pipelines, and generative policy architectures. My work focuses on giving robotic systems the physical intuition required to solve complex, high-precision industrial tasks.
Explore my timeline below to see how I connect deep-tech software engineering with real-world hardware deployment.
💼 Experience :
Master Thesis - Contact-Aware Visuomotor Policies for Robust Dexterous Object Manipulation
Company: Prehensio GmbH
Time: Feb. 2026 – Present
Description:
Currently assigned to the spin-out Prehensio GmbH as part of my ongoing research position at Fraunhofer IPA.
Skills:
Imitation Learning, Tactility, Flow Matching Models, PyTorch, Teleoperation, ROS2, Python, Computer Vision
Research Project - Dexterous Imitation Learning for Vision-Action Models
Company: Fraunhofer Institute IPA
Time: July. 2025 – Feb. 2026
Description:
- Developed a teleoperation and imitation learning pipeline using 3D camera and data glove in ROS2. - Trained Diffusion Policies to enable robust grasping capabilities in multi-object scenes. - Created a full MoveIt model for safe and reliable motion execution planning. - Applied the resulting policies to industrial automation scenarios.
Skills:
Imitation Learning, Diffusion Models, PyTorch, Teleoperation, ROS2, Python, Computer Vision
Research Assistant
Company: Fraunhofer Institute IPA
Time: Jan. 2025 – July. 2025
Description:
Focus on robots with dexterous hands for complex industrial processes: - Developed object pose estimation and tracking algorithms using a multi-camera setup - Integrated solutions into ROS2 and optimized performance with TensorRT and C++ - Improved robustness and accelerated existing model by 10x for industrial deployment
Skills:
PyTorch, Segmentation, ROS2, Python, Computer Vision, TensorRT, Docker
Bachelor Thesis: AI and Large Language Models
Company: SCHUNK – Hand in Hand for Tomorrow
Time: Mar. 2024 – Sept. 2024
Description:
Evaluation and implementation of a retrieval-augmented generation (RAG) approach for product data search using generative AI.
Skills:
Python, LangChain, Vector DBs, ChatGPT, PyTorch, Docker, Linux
Software Engineer (Working Student)
Company: IDS Imaging Development Systems GmbH
Time: Sept. 2023 – Mar. 2024
Description:
Worked on IDS lighthouse, a cloud-based AI vision studio: - Integrated an autolabelling service for easier and faster dataset creation. - Dockerised all services for easier development, testing and deployment. - Evaluated and integrated new SOTA detection models
Skills:
Python, Docker, Git, TensorFlow, Computer Vision, Segmentierung
Intern – Computer Vision
Company: IDS Imaging Development Systems GmbH
Time: Mar. 2023 – Sept. 2023
Description:
- Built multi-language examples for using the REST API of the NXT camera - Developed a cloud dashboard to monitor user performance - Trained and evaluated an image detection model for a client project - Created an AI-based service for image labeling and segmentation
Skills:
C/C++, Python, TypeScript, React, PyTorch, Docker, REST, TensorFlow
Test Engineer (Working Student)
Company: Bosch
Time: Mar. 2022 – Feb. 2023
Description:
Worked on engineering, testing, and development of hydraulic systems.
Skills:
Engineering, Testing, R&D
Student Assistant
Company: Heilbronn University – Center for Industrial AI
Time: Jun. 2022 – Dec. 2022
Description:
Assisted in hardware prototyping and embedded projects
Skills:
C, C++, Python, Arduino, Raspberry Pi
🎓 Education :
Master of Science – Autonomous Systems
Institution: University of Stuttgart
Time: Sept. 2024 – Jan. 2027
Description:
- Research project at Fraunhofer IPA on imitation learning of human grasping tasks with a dexterous robotic arm for industrial applications - Benchmark for evaluating SOTA VLMs on logical game related problem-solving challenges - Literature review on Visiomotor Policies and Vision-Language-Action Models for Robotic Manipulation - Literature review on the application of generative AI in large-scale codebases
Skills:
Foundation Models, Computer Vision, Robotics, Deep Learning, Reinforcement Learning, Artificial Intelligence, LLM
Bachelor of Engineering – Mechatronics and Robotics
Institution: Heilbronn University
Time: Nov. 2020 – Aug. 2024
Description:
Bachelor's thesis GPA: 4.0/4.0 Topic: Retrieval-augmented generation (RAG) for product data search with generative AI Seminar: Time series prediction of chaotic double pendulum using neural networks Projects: - Traffic sign recognition with CNN - Chatbot using LSTMs
Skills:
TensorFlow, Machine Learning, Python, Fusion 360, C++, PyTorch, Git, Time Series Analysis, Image Processing, Robotics, MATLAB, CATIA