Sven Köhler, M.Sc.

 DL Software Developer (full time) – University Hospital, Heidelberg

•  Research Topics: vision recognition, semantic segmentation, spatial transformers and optical flow in the domain of CMR images of children with congenital heart defects

 DL Research Assistant (part time)- University of Applied Sciences, Ma

•  Research Topics: Deep learning, image analysis, technical drawings, Image classification, text & symbol detection/recognition
• Master Thesis: Deep learning, motion analysis, CMR data of patients with congenital heart diseases, semantic segmentation, model generalisation, optical flow, surveillance prediction

DL Software Developer (part time) – SAP SE, COE Deep Learning

• Improvements of general text classification models
• Development and research of fair DL principles

ML Software Developer (part time) – SAP SE, Machine Learning Platform

• Bachelor Thesis: Implementing different ML models as RESTful service
• Classification, compression and visualization of text data

University of Applied Sciences, Mannheim
Software-Engineering: Master of Science

 University of Applied Sciences, Mannheim
 Computer Science: Bachelor of Science

Koehler, S., Hussain, T., Blair, Z., Huffaker, T., Ritzmann, F., Tandon, A., Pickardt, T., Sarikouch, S., Latus, H., Greil, G., Wolf, I., Engelhardt, S.
Unsupervised Domain Adaptation from Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks
In: IEEE Transactions on Medical Imaging 2021

Koehler, S., Tandon, A., Hussain, T., Latus, H., Pickardt T., Sarikouch, S., Beerbaum, B., Greil, G., Engelhardt, S., and Wolf, I.
How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalize to rare congenital heart diseases for surgical planning?
In: Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113151K (16 March 2020)

Scholarship for education and training abroad. Awarded by the German Academic Exchange Service (DAAD).

Selected for the SAP Fast Track program.

Upgrading Masters Scholarship of the Federal Ministry of Education and Research (awarded by the SBB).

 Selected for the Design Thinking Masters program with Stanford (ME310). Topic: Sustainable logistic concepts based on latest technologies.

Upgrading Scholarship for the first academic degree. Funded by the Federal Ministry of Education and Research (awarded by the SBB).