Nadezhda Prodanova

- Designed and developed an algorithm for a medical application, carrying out the entire project cycle including delivering the production-ready code and fulfilling certification requirements. - Developed an internal RAG (Retrieval Augmentation Generation) tool that reduces a separate team’s workload from days down to hours.

- We created a platform for German news with the goal of engaging young people in reading news from trusted sources that cover diverse perspectives. - We won a place in CyberLab- the largest IT-accelerator in Baden Württemberg, against 30 other teams. Additionally, we were awarded the EXIST scholarship.

- Delivered a semantic segmentation solution for a production line which led to acquiring the client and subsequently building the solution for production use. - As part of the ”Autonomous Driving” team I developed the back-end of a computer vision tool, which involved the implementation and integration of deep neural networks for image classification.

Worked on a micro-service for an automatic document generation.

Extracted nerve structures from confocal microscope recordings of the human cornea utilizing classical computer vision methods. Subsequently, this work served as the basis for my bachelor’s thesis, which focused on classifying cornea tissues using machine learning methods.

Developed a cross platform application which provides audio feedback for graphical study materials for visually impaired students.

Master of Informatics with the Profile "Artificial Intelligence"

Unsupervised Domain Adaptation for Ultrasound Speed-of-Sound Reconstruction

Bachelor thesis: Tissue classification of the cornea with convolutional neural networks