Projects, FHNW School of Computer Science

National AI Initiative for Precision Oncology

Turning ordinary homes to smart homes to detect and prevent falls for older adults

This project explores how robotic assistants can be meaningfully integrated into care homes. Together with caregivers, it develops safe and practical solutions that relieve staff and support quality of care.

Ensuring continuity, coordinating the implementation, and shaping the future of Europe’s leading conference on requirements engineering REFSQ.

Photos and floor plans are transformed into realistic 3D models that allow prospective tenants to explore apartments spatially and intuitively.

This AI assistant is designed to support older adults before and after surgery and help detect, prevent and treat cognitive impairments at an early stage.

LiSi brings professional lighting systems to the web: By combining web based system configuration with physically accurate light simulation in real-time, the project enables interactive and lighting design directly in the browser.

An AI-assisted approach to radically simplifying requirements elicitation and the configuration of enablerr, a fully configurable no-code business software platform for orchestrating digital business processes. By combining automated, customer-specific configuration proposals with continuous monitoring and feedback, the approach lays the foundation for faster, smarter, and more scalable customer onboarding.

We are advancing cultural heritage digitization by combining state-of-the-art 3D capture techniques with automated processing, streaming, and real-time rendering — delivering museum-grade visual quality for immersive exploration directly in the browser.

The project develops a digital assistant that helps planning professionals select suitable solutions for structure-borne sound insulation and vibration protection.

Scalable GenXR—Generative AI for Extended Reality—explores novel methods for transforming one or a few 2D product images into high-quality 3D models for augmented and extended reality. The project aims to enable largely automated, scalable and sustainable 3D content creation for retail and beyond by reducing manual processing and improving energy efficiency.

We contribute to the IMPORTANT medical study with a tool-supported method for patient-centred recruitment. The study aims to improve breast cancer treatment for older patients by combining real-world evidence to reduce treatment-related toxicity.

Field workers often make decisions by mentally translating 2D maps into complex real world environments. This project explores how Augmented Reality can support more intuitive, in situ interaction with geospatial data. Grounded in user research, it aims to improve spatial understanding and decision making directly in the field.

Empowering young people to understand, critically assess, and use AI responsibly: the ASGD project develops a tool-supported workshop for equipping the next generation with the skills they need to navigate and shape an AI-driven world.

To support load management and energy procurement for a distribution network operator, FHNW has developed a practical tool.

The FHNW Institute of Interactive Technologies develops a marketplace for the open development of systems of artificial intelligence (AI). The marketplace allows connecting in-house AI pipelines with the AI pipelines of partner companies for collaboratively developing AI systems in a controlled and trusted manner.

The FHNW Institute of Interactive Technologies develops a new generation of interfaces that transform traditional surfaces like tables into interactive environments.

Research participant recruitment, data collection and mapping STEAM initiatives in Switzerland.

Application of state-of-the-art NLP models increases efficiency of third party patent monitoring in the nutrition and bioscience industry.

Swiss German is a difficult language to transcribe. Our project has resulted in an easy, commercially available tool for transcribing and translating Swiss German into Standard German.

The Spectrometer / Telescope for Imaging X-rays (STIX) is an X-ray telescope that makes images and spectra of solar explosions called flares. It is one of the 10 instruments on board the ESA spacecraft Solar Orbiter.

A newly developed diagnostic tool enables real-time remote monitoring of complex manufacturing systems worldwide.

Building Automation in the Age of the Internet of Things (IoT)

Buildings in Switzerland use about 40% of the country's energy. We are developing a system to create digital models of physical buildings to make the renovation process more efficient.

A software infrastructure that enables efficient and robust pipeline processing of the vast amount of data in distributed processing sites.

Gaming with elderly people

Machine learning methodology to detect, analyse and possibly predict solar flares from data provided by NASA's space telescope IRIS.

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.

Buildings in Switzerland use about 40% of the country's energy. We are developing a system to create digital models of physical buildings to make the renovation process more efficient.

When you build the world’s largest telescope, you end up collecting an astronomical amount of data. We help the international mega-science project SKAO manage its Big Data.

Switzerland is active in space, but many don’t know it. Our public engagement programme shares information and encourages people of all ages to explore space actively.

Thanks to machine learning algorithms, defects along the production chain of hybrid photon counting (HPC) detectors can be detected and eliminated early.

The FHNW Institute for Data Science researches the use of generative deep learning-based language models to create tailored texts.

Application of state-of-the-art NLP models increases efficiency of third party patent monitoring in the nutrition and bioscience industry.

The School of Engineering FHNW has developed a method to support operators of AXPO hydro power plants.

For the RHESSI satellite we develop an algorithm to reconstruct X-ray images of solar flares.

According to a 2014 study, 30% of all teachers in Switzerland are at risk of burnout. With TEATIME, we are developing a smartphone app to promote the mental health of teachers.

The School of Engineering FHNW has developed an elaborated matching method for the innovative start-up Yooture.

An innovative solution for the estimation of characteristic values for the construction and real estate industry for the start-up company ‘kennwerte ag’.

A system for extracting relevant information from medical reports in order to report side effects of drugs semi-automatically to the responsible authorities.