Projects

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.

This project studies new dependently typed systems suitable for the development and mechanization of programming language semantics. Particular emphasis is given to languages supporting concurrency and non-determinism, such as transition systems and process calculi. Popular proof assistants based on dependent type theory, such as Agda and Coq, are inadequate for the formal verification of the denotational semantics of such languages because of their insufficiently expressive type systems. We address this issue by extending modern type-theoretic frameworks, such as homotopy type theory, with a new class of coinductive types coming from final coalgebras of accessible functors. In denotational semantics, these types are necessary for handling the non-deterministic and continuously-interactive behavior of processes. The resulting more expressive type systems will prove themselves capable of encoding the formal semantics of various languages with concurrency and non-determinism.

The goal of the project is to develop and integrate a personal student assistant based on large language models (e.g. GPT) into the learning environment of Tallinn University of Technology (TalTech). The assistant will be connected to the university's Moodle learning environment and will be able to provide fast and personalized feedback, helping students with course completion and solving assignments.

The ENACT (https://enact-eu.net/) strengthens crime prevention and counter-terrorism efforts by supporting cutting-edge technologies like the Drug Hunter Analyzer. Developed by TalTech and the Estonian Police and Border Guard Board, Drug Hunter enables fast and reliable on-site drug detection in oral fluid within minutes. ENACT funding aims to enhance the visibility of Drug Hunter by supporting pilot studies, validation, and dissemination efforts, ensuring its successful adoption in law enforcement and forensic applications.

The WaveTwin project aims to further develop a digital twin for estimating the wave state in the Baltic Sea from Synthetic Aperture Radar (SAR) data. Previous methods for SAR data are not successful enough for enclosed water bodies where steep wind waves are dominating. It is apparent that the Baltic Sea also cannot be covered fully with wave buoys to measure the energy spectrum, i.e. the distribution of wave energy by frequency. The use of SAR data allows us to effectively evaluate the wave spectrum over the entire Baltic Sea, skipping the high costs of installing and operating wave buoys. To achieve this goal, the team will use their expertise in the application of deep learning techniques to estimate wave spectra based on SAR images. Environmental protection and navigation at sea (e.g. for the construction and maintenance of wind farms) are two of the most important application areas. A growing interest in such problems is also evident in the field of situational awareness systems.

The purpose of the project is to demonstrate the usefulness and added value of the data layers being created and thereby strengthen the capacity of Estonian industry in the use of EO data. The research and development activities of the project are aimed at: (1) artificial intelligence-based software development for estimating wave parameters in the coastal zone and (2) optimization of InSAR processing capabilities.

Implementation of the IT Academy programme ICT research support project according to three strategic objectives: 1. Increasing the innovation capacity of the Estonian economy and society at large through the smarter use of ICT; 2. Increasing the ICT R&D capacity of universities in priority research areas; 3. Linking R&D with teaching activities at all levels of higher education.

The central research focus of the technology and economics of trust in software theme will be certified software. Topics of research include: • methods and tools for certification of software; program analysis, transformation, generation; in particular for big data, cloud and IoT; • static analysis (model checkers, theorem provers), verification, systematic testing; • contract languages, languages with powerful type systems (refinement types, dependent types); domain-specific languages; • program synthesis and program learning, program understanding; • repositories of certified software, evolution of certified software; • trust in closed-source software, gradual trust-building; • trading trust, pricing of trust, game theory of trust.