High-assurance software laboratory

CORESpaces project will enable a new normal in understanding, co-designing and implementing systemic changes for delivering human centric, resilient, climate neutral, revitalized and dynamically managed urban space, in partnership with citizens and stakeholders. CORESpaces rethinks spaces and public realm by developing and deploying flexibly adjusted, transferable tools demonstrated and tested in 9 cities across 9 European countries, generating open knowledge to streamline diffusion to any city building capacity and skills for climate-neutral, safe and smart urban redesign in EU urban spaces. The project will help to change spaces to become cognitive and future ready for climate neutrality.

Data has become the most valuable resource for the automation and optimization of tasks arising both in the private and public spheres. The proposed research area/project aims at strengthening both the synergy and quality of the current research of Taltech in this area, while significantly enhancing the capabilities of Uni to cooperate with Estonian industry and public sphere by joint work, consultations, continuous and regular education. The focus of the project is on using machine learning for data science: ML, in particular deep learning, has shown the most promise in advancing the capabilities of future software systems and empowering the whole business of software development. The concrete goal is to increase the manpower and competence in machine learning, while enhancing and cooperating with the existing areas of data science like data and rule mining, data semantics and knowledge representation, natural language data queries, data integration, statistics and data management.

The present project aims to develop novel and enhance existing methods of explainable artificial intelligence for the analysis of human motor functions. Pilot studies have demonstrated promising results to support the diagnosis of neurodegenerative diseases. In addition, we plan to extend the area of application from medicine to cognitive development and cognitive fatigue analysis. The integration of the explainer component will provide medical professionals with the necessary transparency of the decisions made by AI. Application in the area of cognitive development to support the school education process. Cognitive fatigue is known to cause severe injuries and serious financial losses. In-depth understanding of this phenomenon and ability to recognise mental fatigue targets to make the work environment safer and reduce monetary and non-monetary losses in the process of work.