
Hey, I’m Elias Baumann, currently a data and validation machine learning engineer at Kaiko.ai. I develop and optimize machine and deep learning models for large scale image analysis in digital pathology. I am also interested in the development of new methods for the analysis of multi-omics data and the integration of these data types for the development of new biomarkers.
In my professional career, I try to develop innovative solutions for problems, where the fundamental understanding of the respective domain is crucial, and therefore also love to learn everything about the problem domain.
I am currently based in Bern, Switzerland but am working in the Zürich office of Kaiko.
Experience
Kaiko.ai
Jul 2025 - Present
Engineer, Data and Validation
University of Bern
Apr 2021 - May 2025
Phd Student, Computational Pathology
RadboudUMC Nijmegen
Mar 2023 - Aug 2023
Visiting researcher, Computational Pathology
Humboldt University of Berlin
2017 - 2020
Research Assistant, Chair of Information Systems
B.telligent
Nov 2015 - May 2016
Intern, Visual data discovery
Telefónica Germany & Co. OHG
Aug 2014 - Oct 2015
Intern, Mobile and web apps
Education
Ph. D. Computational Pathology
University of Bern
M. Sc. Information Systems
Humboldt University of Berlin
B. Sc. Computer Science
Technical University Munich
Competitions & recognition
SGPath
2023
Best Presentation
AI For Climate Hackathon 2021
2021
Winner
Data Science Game
2018
Finalist (Winner of Fair Play Award)
Tools & technologies
Azure
AWS
Visual Studio Code
Adobe Ps , Ai , Id
Eclipse
Office 365
ImageJ, Fiji
Skills
- Python development
- Machine learning and deep learning development
- Image analysis
- Optimization for deployment
- Containerization (Docker, Singularity)
- Cloud (Azure, AWS)
- Statistics and data science
- Bioinformatics
- Research from idea to published paper
- Project Management
About this site
This site has been adapted from the original webiste by Matt Grey on Github which was made available under the GNU General Public License v3.