Fabian Crabus
Hi, I'm Fabian Crabus, an AI Developer with 25 years of experience specializing in Java, Big Data, Python, AI, ML, GIS, and IoT technologies.
About
Hi, I’m Fabian Crabus, an AI Developer with 25 years of experience specializing in Java, Big Data, Python, AI, ML, GIS, and IoT technologies. I’ve led development teams, designed scalable microservices, and worked on innovative projects like real-time container tracking and AI predictive models for maritime logistics. I enjoy creating robust systems that integrate AI and Big Data to solve real-world problems.
I thrive in collaborative environments and am passionate about pushing the boundaries of technology to improve logistics and data analytics. With a strong background in software architecture and AI, I am always excited to take on new challenges and contribute to impactful projects that leverage cutting-edge technology.
- 26 years' experience
- Joined July 2025
Skills· 17
Languages
- GermanFluent
- EnglishAdvanced
Industry experience
- Transportation & Logistics
- Software & Internet
- Professional Services
- Computers & Electronics
- Government
- Manufacturing
Work experience· 20 roles
Led software development and technical implementation for a research project involving real-time container tracking with custom IoT sensors, dynamic geofencing using Tile38, and microservices architecture with Java 17 and Quarkus. Integrated external systems via MQTT and ETL/mapping for port TOS, and developed AI models for predictive container dwell time forecasting based on real-time variables such as load, container type, and weather. Optimized PostgreSQL databases and implemented JWT and OAuth2-based authentication & authorization.
Led software development and technical implementation for a research project focused on real-time container tracking using custom IoT sensors and dynamic geofencing with Tile38. Developed microservices architecture using Java 17 and Quarkus, integrating external systems via MQTT and ETL/mapping for the port's Terminal Operating System. Implemented AI for predictive container dwell time forecasting and optimized PostgreSQL databases. Ensured security with JWT and OAuth2-based authentication and authorization methods.
Led software development and technical implementation focusing on IoT integration for real-time container tracking, dynamic geofencing with Tile38, and microservices architecture using Java 17 and Quarkus. Managed system integration via MQTT and ETL/mapping for port Terminal Operating System. Integrated AI for predictive container dwell time forecasting with real-time variables such as load, container type, and weather. Enhanced data management with PostgreSQL optimization and implemented JWT and OAuth2-based authentication and authorization.
Certifications and awards· 13
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