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This project involves the further development of the lift retrofit system developed by the IPP. The aim is to optimize the product for series production. The IPP is taking the lead in the design, the creation of manufacturing documents, and the support of the procurement of individual parts and…

Every step tells a story – especially in Multiple Sclerosis (MS), where gait reveals important health insights. This project digitizes gait assessments in people with MS using wearable sensors. By comparing therapist-rated outcomes withbiomechanical data, we aim to identify key gait parameters and…

Exploring the political in public health: Perspectives from practitioners and academics about the political determinants of health

This goal of this project is to develop novel hybrid classical-quantum machine learning algorithms to tackle challenging problems in academia and industry on quantum simulators as well as on real quantum hardware.

This empirical research project on road safety follows an innovative participatory approach to examine how schoolchildren perceive hazardous situations on their way to school and in the school environment.

Claims in regulated sectors, such as insurance, remain inconsistent and costly. Manual reviews, static digital forms and opaque systems create inefficiencies, errors and compliance risks, while regulators increasingly demand transparency and speed. This presents an opportunity for a solution that…

We develop an AI-powered platform that makes creating customized equity indices simple, transparent, and cost-efficient. Instead of relying on expensive, predefined benchmarks, users define their investment strategy in natural language. Our generative AI engine interprets these inputs using…

FEAT4AFRICA aims to strengthen food and nutrition security (FNS) in African urban areas by integrating innovative agri-food technologies within a Living Lab (LL) network that facilitates adoption, diffusion, and social acceptance. The project seeks to improve urban food literacy, enabling citizens…

Job satisfaction is imprtant for job retention. In this project, we will identify and describe factors that are associate with the job satisfaction of occupational therapists, physiotherapists and midwives in Switzerland - based on data from the Swiss Cohort of Healthcare Professionals and Informal…

The proposed solution is a digitally-enabled generative design tool for residential real-estate development, systematically integrating data on market information, construction law, topography and site constraints, environmental factors, costs, revenues, and sustainability KPIs.

The integration of real estate data means combining data from all life cycle phases and making it comparable. This creates a benchmark that enhances transparency and enables well-informed, data-driven decisions for the planning, operation, and development of real estate.

This project aims to develop a Generative Artificial Intelligence (GenAI) component for Switzerland’s largest text collection ofpublic communication — Swiss-AL. The component will be based on Retrieval-Augmented Generation (RAG), which enhancesthe transparency of GenAI by allowing it to ground…

Commissioned by Physioswiss and funded by the Swiss Federal Quality Commission (EQK), the project develops a national quality improvement programme for outpatient physiotherapy. For key conditions, scientifically grounded quality indicators and a quality development system are developed, piloted and…

The Care for Rare Navigator develops a digital, AI-supported counsel-ling system for families affected by rare diseases, providing needs-oriented, everyday support that complements existing care structures. Expected outcomes include strengthened orientation and self-efficacy as well as psychosocial…

TESSA integrates AI agents via Model Context Protocol to democratize district heating design. By enabling natural language interfaces, consultants can access advanced thermal simulation and storage optimization without specialist expertise—accelerating the energy transition and supporting…

This feasibility study develops a web-based interface for a novel Traffic Prediction Engine (TPE), enabling highly accurate and fast simulations of urban traffic flows to support data-driven and sustainable transport and infrastructure planning.