Jan Sollmann, M.Sc.

I joined the Chair of Software Engineering after pursueing my Master’s in Applied Computer Science at Ruhr University Bochum from 2020 to 2023, specializing towards Artificial Intelligence, Bioinformatics, and Neuroinformatics. Collaborating with the Leibniz Institute for Analytical Sciences in Dortmund, my Master’s thesis, “Image Compression for Microscopy Images in the Era of AI: Theories, Models, and Applications” explored classical and deep learning-based image compression. This research delved into its implications on predictions of label-free models for microscopic image data, earning acceptance as a poster for the Focus on Microscopy conference in 2023.

Throughout my master’s journey, I engaged myself in diverse projects and labs, including time-optimized path planning for a KUKA robot-arm in MATLAB, application of Transformers for image classification, and the development of a high-throughput pre-processing pipeline for fluorescence images of neurospheres. My expertise extended to using ROS2 with TurtleBots for cone detection, sensor fusion with LiDAR data, and final path planning with the ultimate goal of enabling autonomous driving.

Before pursuing my master’s, I completed my Bachelor’s in Computer Science at Leipzig University of Applied Sciences (2017-2020), specializing in Software Systems and Technical Systems. My Bachelor’s thesis, “Technological Market Analysis of IoT Platforms and Application Possibilities for Optimizing Internal Company Processes” emerged from my role as a working student at EXXETA AG in Leipzig. In this position, I took on responsibilities spanning frontend and backend development, IoT hardware configuration, serverless computing, cloud services utilization, containerization, and project organization.

During this time, I actively contributed to various projects too, including the automatic generation of UML diagrams from source code, microcontroller programming with a focus on logic implementation and encoder/decoder circuits, the implementation of a PID controller in an Arduino vehicle and leader election in a Dezibot robot swarm.

Academic Achievements

• M.Sc., Applied Computer Science, Ruhr University Bochum, 2023
• B.Sc., Computer Science, Leipzig University of Applied Sciences, 2020

Research Fields and Interests

• Multi-Machine Learning Systems
• Autonomous Systems
• Root Cause Analysis, Runtime Monitoring & Field-Based Testing

Publications

Y. Zhou, J. Sollmann and J. Chen, “Deep learning based Image Compression for Microscopy Images: An Empirical Study”, doi: 10.48550/arXiv.2311.01352