Image Processing Experts in Germany

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

Strategic Marketing / New Customer Acquisition (B2B):

• Market and competition analysis: Identified competitors, developed evaluation grids, sketched provider landscape with potential customers, competitors and partners
• Concept for a cross-media, personalized multi-touch campaign
• Developed the multi-touch strategy in different variants with several stages, defined touchpoints, target companies and target people, developed the ideal customer profile and contact ideas
• Designed all individual measures: developed concepts for letters, postcards, landing pages, emails, phone calls and downloads
• Visualized the logic of the contact sequences (flowchart)
• Described the distinction from "account-based marketing"
• Implementation planning: Researched providers for packaging, shipping and landing page software, negotiated terms, recommended tools and partners

Social Media Marketing:

• Target categorization, definition and recommendation for action
• Review and selection of channels
• Concept for channel management
• Developed an 11-week editorial plan (Instagram & LinkedIn)
• Created, implemented and published image and video posts
• Campaign launch, ongoing monitoring and optimization

Search Engine Optimization (SEO):

• Website audit with indexing check
• Ranking, backlink, traffic and competition analysis
• Analyzed search and user behavior
• Consulting on SEO risks during relaunches with domain changes
• Keyword research and recommendations for action

In this project, I was responsible for the design and implementation of a new, modular, and highly scalable test bench platform for an automotive supplier. My focus was on developing a robust system architecture and programming the associated software, with consistent use of UML modeling throughout. This structured approach made it possible to greatly increase the reusability of individual LabVIEW test modules and to significantly reduce development time for follow-up projects. I also integrated modern automotive standards such as CAN FD, LIN, and safety requirements, which made the solution future-proof.

Technologies: LabVIEW, Visio, UML, CAN FD, LIN, DMM, Safety, image processing, project management, HMI, C#, C++, Python, Rust, CI

Development of an iOS app for virtual try-on and outfit suggestions

The goal of the project is to develop a mobile application for personalized, photorealistic outfit suggestions. Users should be able to upload their own photos, try on clothes virtually, and find products that can be bought directly in the generated suggestions.

• Planning and implementation of the onboarding and photo upload in the iOS app
• Development of the mobile application with Expo and React Native
• Implementation of a Hono/Node.js backend for user, product, and generation processes
• Building an asynchronous processing pipeline with BullMQ and Redis
• Connection of PostgreSQL/pgvector and S3 for product, image, and generation data
• Integration of Gemini and OpenAI for outfit generation and image processing
• Implementation of a credit system and integration of RevenueCat
• Integration of Stripe Connect and affiliate product feeds for products that can be bought directly

Label: TypeScript, React Native, Expo, Hono, Node.js, PostgreSQL/pgvector, BullMQ, Redis, S3, Gemini, OpenAI, RevenueCat, Stripe Connect, Docker

• Led strategic software development of fusion algorithms for precise object tracking, trajectory prediction, and environment modeling based on multimodal sensor data (e.g., camera, LiDAR, radar, GNSS, IMU)
• Developed and implemented navigation algorithms for autonomous vehicles, including path planning, obstacle avoidance, and sensor fusion of visual, inertial, and distance-based sensor sources
• Automated extraction and training processes with CI/CD
• Developed and optimized data pipelines and processes in Microsoft Azure using Apache Spark, Databricks, and PySpark
• Developed and optimized embedded software for automotive control units
• Designed latency-critical software for real-time control in robotic systems with RTOS (freeRTOS, SAFERTOS)
• Used the Vector toolchain (CANdela, DaVinci, CANoe) for configuration and diagnostics
• Optimized existing data pipelines and processes (ETL, data warehouse, SQL)
• Developed and trained machine learning models using PyTorch
• Created deep-learning-based object detection and visual SLAM algorithms, trained on combined data from camera, LiDAR, and IMU sensors
• Implemented computer vision algorithms for object detection and classification in robotic systems using OpenCV and YOLO, utilizing synchronized image and depth data
• Implemented behavior-based control systems for autonomous robots using ROS2 Behavior Trees
• Performed testing, release, and integration of sensor fusion algorithms into automotive production programs
• Ensured adherence to proper software development processes and safety standards to guarantee high data quality (MISRA, ISO 26262, ASPICE)

• Automotive SPICE®: all assessments fully achieved
• Agile transformation: V-model → SAFe successfully implemented
• Series release: on-time, quality-assured software delivery for key Volkswagen Group models (including ECE homologation)
• Stakeholder management: internal & external
• Process optimization: implemented a continuous improvement process (CIP) with a tracking system

• Spearheaded the integration of a custom Transformer-based encoder into the AFFGANwriting pipeline, replacing the legacy VGG19 architecture to capture richer, high-fidelity writer-style representations.
• Boosted user-study pick-rates by 40%, demonstrating a significant leap in the perceptual quality and realism of the generated handwriting compared to the baseline model.
• Enhanced OCR performance by 20% by implementing a teacher-student framework that leveraged a TrOCR benchmark model for auxiliary training alignment

• Development and validation of control concepts for grid stabilization with MATLAB/Simulink.
• Modeling of converters (VISMA), grids, and loads to study frequency and phase behavior during load steps.
• Analysis of the influence of inertia, damping, and controller parameters on stability, power output, and ROCOF.
• Development of adaptive control strategies to improve synchronization and dynamic grid support.
• Creation of automated simulation and evaluation tools to assess different scenarios and parameters.

• Developed and implemented AI-based perception and multimodal systems for real-world environments
• Built, trained, and evaluated Machine Learning and Deep Learning models using Python, PyTorch, TensorFlow, and OpenCV
• Worked with Vision-Language Models (VLMs), Large Language Models (LLMs), transformer-based architectures, and multimodal AI systems
• Applied LoRA-based fine-tuning techniques and experimented with diffusion models for generative and multimodal AI applications
• Developed multimodal perception pipelines using camera, LiDAR, and sensor data
• Designed end-to-end workflows for data processing, model training, evaluation, benchmarking, and robustness analysis
• Utilized HuggingFace Transformers and modern Deep Learning frameworks for AI experimentation and deployment workflows
• Applied GPU-accelerated computing, CUDA-based processing, ONNX, and TensorRT optimization for efficient inference and large-scale model training
• Collaborated with industry partners including Valeo and REHAU on applied AI and intelligent system projects
• Developed scalable AI architectures and prototype software solutions for automation and perception tasks

• Development of new simulator features and extension of existing modules using C++.

• GUI design and implementation with Qt for Windows, including redesigns to improve usability and workflow.

• Maintenance and expansion of existing codebase: refactoring, bug fixes, and modularization to support new capabilities.

• Version control using Git.

• Performance optimization of simulation to meet real-time constraints.

• Creating and maintaining documentation: technical comments, design docs, API references and user manuals.

• Led a redesign that improved operator workflow and reduced task completion time.

• Extended simulator architecture to support multiple new scenario types while preserving backward compatibility.

• Implemented refactoring and modularization that simplified maintenance and accelerated feature delivery.

• Technologies: C++03, Qt4.6, QMake, Git, V-Model, Windows

• Add/create test specifications
• Conduct regression tests
• Conduct release tests
• Analyze Jira tickets
• Identify software defects and fix them with C#

• Introduction to AI and Automation
• The Automation Project
• Make.com Foundations
• Automation Basics: Data Management
• Document Workflows, Troubleshoot, and Automate Reports
• Digression: Data as the Foundation of AI Systems
• Implementing AI Solutions in Practice
• Digression: Large Language Models (LLMs)

• Designed and implemented the complete data flow architecture for the Mercedes-AMG battery case production line, from raw material processing to end-customer traceability.

• Developed MQTT-based communication protocols for Siemens S7 PLC controllers to enable efficient real-time data exchange between machines and supervisory systems.

• Architected a local Ubuntu-based industrial server, integrating Node-RED for data collection, MySQL databases running in Docker containers, and automated data pipelines.

• Commissioned connectivity of 52 Siemens PLCs and 32 Yaskawa welding and handling robots.

• Designed and implemented HMI and visualization systems to support operator interaction and production monitoring.

• Designed a 2D digital twin of the production floor, visualizing real-time process data from 26 Siemens PLCs and 18 Yaskawa welding robots via Stromquelle interfaces.

• Implemented data collection and camera-based measurement systems for welding quality control and automated defect visualization.

• Designed and optimized MySQL database structures, including stored procedures for data processing and performance analytics.

• Built a modular C++ 20 embedded Linux acquisition system on a Raspberry Pi, synchronizing IMU and dual-camera data streams to sub-millisecond accuracy.
• Integrated retro-reflective and contrast sensors to trigger acquisition and detect gaps between sorter rails.
• Implemented SPI & I2C sensor communication, GPIO interrupt handling with libgpiod, and CSV & JSON output.
• Designed a multi-threaded acquisition pipeline and an SPSC queue between acquisition and writer threads.
• Built a Python/HTML/CSS based web-server and validated the prototype in a DHL warehouse for defect detection.
• Documented software behavior, configuration, and results for maintainable handover and further development.