• Implemented new features into GUI-Tools
• Supported working students and new employees

Developed, implemented and applied for a patent

• For a new, lossless raw image compression format optimized for real-time GPU raw image compression and decompression
• Achieved 15% smaller footprint and faster processing than competing format

Optimized and improved quality of existing image-processing pipeline

• Achieved over 2x aggregate performance in CUDA by overhauling every kernel
• Also helped enable multi-GPU support and asynchronous processing

Implemented and contributed to new algorithms

• Contributed to a machine-learning based dead pixel detector
• Contributed to noise reduction and demosaicing algorithms
• Developed a nvidia tegra CUDA based internal test station
• Helped make new algorithms real-time capable

• Faculty for Experimental Physics with Cosmic Particles (ECP)
• Implemented features necessary for new detectors into simulation framework

Ported CPU- based analysis and Reconstruction tools to CUDA and OpenCL

• Achieved significant improvements in processing speed by GPU processing and by restructuring programs
• Reduced processing time of an in-use algorithm from hours to seconds while enabling increased precision

Contributed to new reconstruction and analysis tools

• Developed awareness of the deteriorating effect of common pseudo-random number generators on simulation-generated control data
• Helped improve understanding of the effect of machine precision on algorithms

Self-employed through personal recommendation. Concurrently to university studies.

• Tutored a total of over 120 students in Math, Physics, Chemistry and Computer Science in all grades and schools
• Developed communication and motivation skills
• Experienced quite a few surprises