Key data
Activities
- Scientific Assistant
- Collaboration in applied research and industry projects in the fields of applied machine learning and data-driven systems
Expertise
Applied Machine Learning
Time-series modelling and data-driven optimization
Image processing & computer vision
Reproducible ML workflows and data engineering
Selected projects
Marvel: Real-time pollen information
Together with our project partners, we develop zero-shot learning and other machine learning tools for recognising pollen particles anywhere in the world. As a result, it will be easier to create reliable pollen weather forecasts.
2024–26: Forecast-based energy and greenhouse gas management for wastewater treatment plants (with Hunziker Betatech AG, Institute for Automation; funded by Innosuisse)