Projects

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  • Biomarkers for depression

    Project start / May 01, 2022

    We aim to validate and commercialise biomarkers and the resulting products for affective disorders to address the many unmet needs along the entire disease trajectory.

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  • © Fraunhofer SCAI

    To develop hardware such as microprocessors, field-programmable gate arrays (FPGAs) are typically used. However, optimizing the interconnection of these logic devices is itself a difficult problem for Turing machines (the so-called Quadratic Assignment Problem or QAP). Quantum or quantum-inspired hardware seems to be a better way to solve this problem. The approach in the QuantumQAP project is to combine quantum hardware and theoretical solution approaches that are applied in the two application fields of FPGA interconnection and post-quantum cryptography.

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  • TransHyDE-Sys − System Analysis of Transport Solutions for Green Hydrogen

    BMBF-Project / Project start / April 01, 2021

    © Fraunhofer SCAI

    One approach in the context of the energy transition is to also feed green hydrogen into the existing German network for gas transport. In order to be able to plan, control and analyze such scenarios, existing simulation models must be extended so that they can represent gas mixtures with high hydrogen content. In addition, the coupling to the relevant power grids must be advanced. These are the goals of the TransHyDE-Sys project. This project is part of the BMBF flagship project TransHyDE.

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  • The European project DIGIPD, funded with around 1.6 million euros and coordinated by the Fraunhofer Institute for Algorithms and Scientific Computing SCAI, is investigating the extent to which digital techniques (sensors, speech recognition, recognition of facial expressions) can be used to make a more precise and individualized diagnosis and prognosis of Parkinson's disease. The project is funded by the European network for personalized medicine, ERA PerMed, in the "Joint Transnational Call 2020". The German share of DIGIPD is funded by the Federal Ministry of Education and Research (BMBF).

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  • The zet-o-map project aims to develop better tools for the identification of teratogenic compounds. One of the most promising assays is the zebrafish embryo teratogenicity assay (ZETA). In human risk assessment the evaluation of developmental toxicity or teratogenicity requires the testing of rodents (preferably rats) and non-rodents (preferably rabbits) as described in the OECD 414 guideline. Currently human safety assessment is undergoing a paradigm shift moving towards mechanistic risk assessment and there is a high demand to replace, reduce or refine animal tests where possible for ethical and economic reasons. zet-o-map is funded by the Long Range Research Initiative (LRI) of the European Chemical Industry Council (CEFIC).

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  • Fraunhofer HABICHT

    Project start / February 01, 2021

    © Fraunhofer SCAI

    High-speed drive for fuel cell air compressors in commercial vehicle and aviation applications.

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  • Optimization of Logistics and Production Processes

    Project start / January 01, 2021

    © tiero - stock.adobe.com

    The dynamic optimization of logistics and production processes in real time is at the top of the wish list of many small and large companies in order to gain a significant reduction of costs while improving machine utilization, workload distribution and product delivery times. Using the example of a fictitious warehouse, it can be shown which optimization measures interlock with each other and how complex processes become manageable even for small companies.

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  • Biomedical Knowledge Graphs

    Project start / January 01, 2021

    Biomedical knowledge graphs play a central role in big data integration. Bringing unstructured text into a structured, comparable format is one of the key assets. As cause and effect models, knowledge graphs can potentially facilitate clinical decision making or help to drive research towards precision medicine.

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  • A sustainable circular economy is essential to achieve the goal of climate neutrality. To this end, the development of new innovative building materials is crucial. However, this development has so far been a very laborious and lengthy process. To support and significantly accelerate this process, experts from the Fraunhofer institutes IBP and SCAI develop new data-driven virtual techniques for material design at the Fraunhofer Center for Machine Learning.

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