Developed an integrated software suite analyzing X-ray electron beamline data. Directed technical strategy and system architecture web app, backend, and IoT device. Streamline the tech stack for faster delivery of more high quality features. Cultivated a learning environment, enhancing team technical skills and proficiency.
Technologies:
Focal Point: MVP for improved data mgmt. and collaboration in scientific research.
Focus on software projects and technologies for learning purposes. Experiments: Telling a story about a problem of high abstraction using visual animations to synthesize environmental characteristics and related properties.
POC: OSGi v7 and 8, OSGi in Docker, OSGi with Graal / Native Image, Neo4j in OSGi. OSS: Contribution in various OSS projects e.g. Millipede (large Nextjs app), JClouds.
Technologies:
Babysteps: ML frameworks and OpenAPI. Focal Point: Fn programming.
Lighthouse project to enable digital transformation in real estate finance. Web-based application that reflects the entire loan origination process. Real-time calculation pipeline to determine crucial figures fully autonomous. Transform slow work routines into smart, decision-supported collaborative workflows. Boost onboarding experience of new users through reactive cross-app interactions.
Technologies:
Assistant technologies to enable self-determination in the digital world.
Cloud synchronization application with a focus on security and abstraction of storage. Distributed communication and coordination middleware. Native FS Integration. Social context and storage aggregator for 13 Social-Media and 12 Cloud Platforms. Browser Ext. to embed a secure sharing context into an arbitrary digital environment. Desktop-based application (Electron) based on web- and native technologies. API for third-party utilization (REST, Vert.x and GraphQL). Automated (Standalone / Docker) local/remote backend deployment (Cloud Sync)
Technologies:
Privacy Enhancing Technology
Task: Research and development to improve P2P applications
Goal: Improve P2P-based (BitTorrent) data transfer model with client/server models
Requirements: P2P Protocol Modification, Modularization, Modern User interface (RIA)
Challenge: Refactor large/complex applications to share a modularization concept
Technologies:
Task: Development of a real-time image/pattern recognition from scratch
Goal: Improve labeling equipment to avoid cutting marks on the badge of PET bottles
Challenge: Recognition rate which corresponds to reality - 8 m/s - 50K badges/h
Technologies:
Discover other experts with similar qualifications and experience