About me
I am a Senior Data Scientist at the Deutsches Biomasseforschungszentrum (DBFZ) in Leipzig, where I pair theoretical physics training with hands-on AI and HPC engineering. I design neural and probabilistic workflows for complex research questions, run Slurm-based clusters with containerised pipelines, and automate deployments via GitLab/GitHub Actions. Alongside institute projects I build open-source tools—most notably ScrAIbe and ScrAIbe-WebUI—to make accurate transcription infrastructure available to non-coders. I mentor students through thesis supervision, workshops, and long-standing teaching at the HASP student laboratory, and I am now looking for a PhD that lets me push this interdisciplinary mix even further.
Experience
Senior Data Scientist & AI Advisor
Steering AI strategy for sustainable energy research
I lead applied data science projects at the Deutsches Biomasseforschungszentrum (DBFZ), helping research groups unlock value from complex bioenergy datasets. My role combines high-level advisory work with hands-on implementation across the machine learning lifecycle.
- Design data and machine learning strategies that align with project goals, funding requirements, and ethical guardrails.
- Build and maintain reproducible analytics pipelines that empower researchers to iterate quickly without compromising rigour.
- Shape the institute’s AI-HPC roadmap, selecting tooling and infrastructure that balance performance, cost, and long-term maintainability.
- Mentor interdisciplinary teams on best practices in data governance, documentation, and collaborative experimentation.
- Introduce probabilistic reasoning methods and calibration routines that raise confidence in model predictions for policy-facing research.
- Lead the operation of Slurm clusters, container stacks, and GitLab/GitHub automation, including CVE-driven patching and security monitoring.
- Build open-source tooling such as ScrAIbe and ScrAIbe-WebUI so non-coders can access transcription and diarisation pipelines.
This position allows me to bridge theoretical physics training with real-world impact, ensuring that machine learning accelerates rather than obscures scientific insight.
Student Council Representative (Volunteer)
Advocating for students and shaping academic initiatives
While completing my studies, I volunteered as an elected member of the physics student council, where I supported peers and liaised with faculty on academic and organisational matters.
- Represented student perspectives in departmental meetings and curriculum discussions.
- Coordinated events that connected students with research groups and external partners.
- Helped streamline communication between cohorts by introducing shared documentation practices.
The experience strengthened my facilitation skills and reinforced the importance of inclusive, transparent decision making in academic environments.
Scientific Assistant
Inspiring future physicists through hands-on experimentation
Since 2016 I have supported the HASP student laboratory, where we introduce young students to experimental physics. My work spans curriculum design, experiment setup, and on-site mentorship.
- Develop accessible explanations of complex physical phenomena tailored to different age groups.
- Build and refine experimental setups that balance safety, robustness, and scientific accuracy.
- Guide visiting students through experiments, encouraging curiosity and critical thinking.
- Coordinate with university staff to expand the laboratory’s catalogue of demonstrations.
This long-term role keeps me connected to teaching and science communication, and continually sharpens my ability to translate advanced concepts into approachable learning experiences.
Education
Projects
Publications & Presentations
- Poster — “Numerical Information Field Theory for Acoustic Monitoring,” Helmholtz AI Conference, Karlsruhe (2025)
- Talk — “KI für kritische Infrastruktur: Open-Source-Lösungen für Verwaltung und Industrie,” Data Week Leipzig (2025)