FHNW School of Computer Science

Each year, we initiate dozens of new research and development projects with industry partners. Companies can also collaborate with us through student projects and bachelor’s or master’s theses, where our students tackle complex challenges – with minimal financial effort for your organisation.

Together with our partners, we are developing zero-shot learning and other machine learning tools to identify pollen worldwide. This makes it easier to create reliable pollen forecasts. The Marvel project is a great example of how a university of applied sciences works: we use cutting-edge technologies and find practical applications for them. As a result, our industry partner gains a solution that can be commercialised immediately. And people with pollen allergies around the world will soon have access to even better forecasts and warnings.

For our partner AXPO, we are successfully developing an analytical solution to evaluate maintenance scenarios for individual hydropower plants. The model, implemented using linear programming, achieves a level of predictive accuracy that is comparable to that of stochastic dynamic programming models for most plants and scenarios. Due to the drastically reduced computational costs, our solution is highly suitable as an interactive planning tool

Countries around the world have joined forces to investigate fundamental scientific questions across a wide range of fields. The FHNW School of Computer Science is part of the Swiss team SKACH in the international research project for the Square Kilometre Array (SKA), one of the world’s largest radio telescopes. With our expertise in high-performance computing, we support the project by developing algorithms, integrating pipelines and optimising performance.

On behalf of the Federal Department of Foreign Affairs (FDFA), the FHNW School of Computer Science is exploring the potential of modern language models for the automatic generation of speeches. We analyse the use of state-of-the-art models and experiment with prompts to generate coherent and contextually appropriate text passages. The aim of the project is to evaluate the potential of generative AI for creating tailored speeches and to demonstrate its practical applications.