TalTech AI Center of Excellence

Applied Artificial Intelligence Group

The Applied AI Group conducts research in application of AI methods in various fields and systems. We investigate applicability of machine learning, ontology based reasoning, automated theorem provers, knowledge discovery and other AI methods for solving digitalisation problems of different industrial and governmental stakeholders.

Our previous research has been concentrated on building software development methods and tools (e.g. CoCoViLa) with AI components, basically with program synthesis and ontology based knowledge representation components.

Biosignal Processing Laboratory

The research group is experienced in the interdisciplinary area of information technology and brain physiology. The studies are aimed to detect and interpret the features in the brain electroencephalography (EEG) signal characteristic for mental disorder, occupational and/or environmental stressors comprising the advanced methods of signal analysis and the knowledge about brain neuronal activity. An original Spectral Asymmetry Index (SASI) has been developed and proved as a promising method in various applications.

Business Information Technology Group

The main activity of the Business Information Technology group is the development and analysis of business IT solutions, theories and practical solutions for reliable, interoperable, and evolving applications, and the advancement of future specialists’ education.
The group’s primary research area is methodologies, tools, models, and best practices related to the design, development, and maintenance of enterprise information systems. Currently, the focus is mainly on models used in information systems in the fields of education and healthcare, the validation of these models, and methodologies for their use. The main research topics are data, enterprise information systems, and educational and medical informatics.

Research Laboratory for Cognitronics

The Research Laboratory for Cognitronics develops methods and techniques for miniaturized actuators and sensor technologies (e.g. macro- and microscale actuators and smart multiscale sensors for Lab-on-a-Chip realizations); ressource-constrained implementation of wireless connectivity technologies (e.g. transient and approximate computing in low power wide area networks/IoT); and methods for exploitation and implementation of sensors in data processing and artificial intelligence (e.g. machine learning) for decision-making and actuation.

Laboratory for Compositional Systems and Methods

The group’s goal is to study compositional techniques in the context of models of computation, understood broadly. Compositionality means that syntactic descriptions for (open) systems are designed to be compatible with their semantics. While the examples motivating the research come from a broad section of scientific disciplines (logic, control theory, formal language theory, business processes, game theory, economics, machine learning), we have identified common principles for reasoning about open systems, guided by category theory. These include a semantic universe based on relations rather than functions, and the use of the diagrammatic syntax of string diagrams. String diagrams provide an intuitive calculus for computations via diagrammatic reasoning, and fine-grained control over resources, which is important for faithful descriptions of open systems.

Centre for Digital Forensics and Cyber Security

TalTech Centre for Digital Forensics and Cyber Security works towards raising Estonian cyber security competence and capacity through education, research and knowledge transfer. The research team includes experts from various scientific disciplines, including computer science, law and psychology. Such a team can take on today’s complex cyber security issues that require an interdisciplinary approach.

The main research directions of the Centre are:

• critical Information Infrastructure Protection (focus on eGovernance and transportation sectors);
• cryptography;
• network monitoring;
• digital forensics;
• education research;
• cyber security strategy and policy.

eHealth applications and services Research Group

The main activity of the research group is research in fields related to health data models, clinical decision support, evaluation of digital health technologies, online behavior related to personal health data, and the components and factors of healthcare digitalization. More specifically, the group focuses on the quality, architecture, and data models of digital data used in medicine and healthcare, the evaluation and application areas of digital health technologies, and the development of a reimbursement framework for digital health solutions. Research on IT solutions related to personalized medicine is also ongoing.

Embedded AI Research Lab

The Embedded AI Research Lab focuses on developing machine learning solutions in the embedded systems. The laboratory collaborates internationally with research teams and companies from the maritime, medical, smart city, autonomous vehicles and industrial automation sectors.

High-assurance Software Laboratory

High-assurance Software Laboratory studies theories, methods, and tools for developing highly dependable software, specializing in both formal verification (certified software) and testing. In recent years, applied machine learning has emerged as a separate research area.

Information Systems Group

The Information Systems Group conducts research in large- and ultra-large-scale IT systems. We investigate the architecture, design, realization and management of IT system landscapes, high- volume data-intensive systems, high-volume workflow-intensive systems, massively resource-intensive systems and highly distributed systems. In particular, we investigate the next generation of digital government technologies and digital government ecosystems. Together with our partners from industry, academia and the public sector we strive for excellent solutions for non-standard, mission-critical IT system problems.

Centre for Intelligent Systems

Centre for Intelligent Systems focuses on control systems, artificial neural networks, fractional-order modeling and control, and virtual reality. The research of the group focuses on development and implementation of novel efficient control techniques for Industry 4.0 applications based on the combination of classical industrial controllers with computational intelligence methods and knowledge based reasoning.

Creativity Matters Research Group

Creativity Matters research group at Taltech IT College is a multidisciplinary team that focuses on IT didactics in higher education. Our main research lines are: using telepresence and personal assistant robots in higher education and healthcare; innovative blended and online teaching methods; STEAM approach integration into IT teaching.

Laboratory of Language Technology

One of the important activities is the creation of speech technology applications targeted at society as a whole. This includes applications of end-user speech recognition as well as the key integration components that are easy to integrate. Although the focus is on speech recognition in Estonian, most of the software created in the laboratory is not specific to Estonian. The laboratory is a solid open source free software supporter.

Measurement Electronics Research Group

Measurement Electronics Research Group of Thomas Johann Seebeck Department of Electronics at Tallinn University of Technology (TalTech) performs R&D on various test, measurement and data acquisition solutions.
The research team has long-term experience in developing impedance spectroscopy-based measurement solutions for medical / healthcare as well as materials science, industry and other applications. The history of impedance measurement at the University of Technology dates back to the 1930s (Paul Plakk’s work on the applications of physical chemistry) and the 1980s (vector voltmeters – Mart Min, Toomas Parve).

The research group has been engaged also in the R&D of solutions based on image processing (3D laser scanners, medical image processing with machine learning – O.Märtens – in cooperation with doctoral students (Tõnis Saar, Ago Mõlder, Anindya Gupta and others).

The members of the research group are the authors of hundreds of scientific articles, dozens of book chapters and tens of inventions.

Next Gen Digital State Research Group

The Next Gen Digital State (NGDS) research group addresses the technological complexities of how governments can satisfy the current and future needs of their citizens. We focus on digital government ecosystems by investigating technologies that support digital transformation, innovation and implementation.

Our research group collaborates with Estonian and international public sector agencies, ministries, and departments for developing next-generation government-technology through cutting edge research topics focused on artificial intelligence architecture, requirements engineering, data analytics, and understanding the socio-economic effects of technological implementation. We strive to be on the forefront of public sector innovation research!

Nonlinear Control Systems Group

The group is a leading Estonian research unit in automatic control, focusing on nonlinear control systems, including non-smooth, hybrid and time-delay systems. The group has made a significant contributions to the development of constructive algebraic methods and the associated symbolic software package NLControl, which supports research, teaching and applications.

A universal algebraic methodology has been developed that simplifies the study of very different problems for nonlinear control systems from unified perspective. The main idea is to construct sequences of subspaces (or submodules) of differential 1-forms that provide a lot of information about the structural properties of the system. For instance, an event-based resource-aware control method based on the concept of differential flatness has been developed.

Although the group is developing predominantly application-independent general methods determined by the dynamic properties of the mathematical models, we have been recently focused on a few carefully chosen applications, some of them addressed within the joint topics in the Estonian Centre of Excellence on IT, our group is part of. These include control of autonomous underwater vehicles and ionic polymer-metal composite actuators. Within the last few years, special attention has been paid to the study of practical problems arising in limits of renewable energy integration, and determine the possible limitations of distributed energy storage devices in low inertia power systems utilizing methods from optimal control theory.

Laboratory for Proactive Technologies

The laboratory focuses on theoretical and practical study of networked systems built from stationary and/or mobile software-intensive (proactive) components. Typical components are pervasive computing systems. The research is partitioned into three threads: (1) modelling and verification of situation-aware interaction-centred computation; (2) methods and technologies for acquiring situational information; (3) methods for interpretation of situational information for (proactive) decision making. The long-term goal of the laboratory is the ability to detect and partially control the emergent behaviour in pervasive computing systems.

In addition, ProLab performs research on classification, semantic segmentation and object detection using convolutional neural networks. The methodology has been applied to photographic images, point cloud collections and sound recordings.

Sensor Technologies in Biomedical Engineering (SensorTechBME) Research Group

The main research field of the SensorTechBME team is to develop flexible and novel sensor technologies and algorithms in biomedical engineering applications:

• To estimate dialysis adequacy and quality securing end stage renal disease (ESRD) patients’ care quality. The research is exploring spectrophotometrical and pectrofluorimetrical characteristics-signatures of the biofluids and performing various signal processing and analysis on those signals.
• To develop beyond the state-of-the-art applications incorporated into a smart wearable multi-sensor fusion system for generating valuable data about the workers’ location, locomotion, physical activity, energy consumption and physiological status.
• For speech-to-text usage in healthcare and industry.
• Innovative psychophysiological development of methods that combine quantitative physiological and subjective psychological indicators to assess people’s emotional response to different (living) environments (e.g. safe, comfortable, stressful, overstimulating or unattractive). One area of application is to bridge the gap between city planners and city residents using the so-called well-being score mapping.

Centre for Trustworthy and Efficient Computing Hardware

The Research Centre focuses on cross-layer reliability and self-health awareness technology for tomorrow’s complex intelligent autonomous systems and IoT edge devices in Estonia and EU. The team studies advanced cyber-physical systems characterized by their heterogeneity and the emerging computing architectures employing AI-based autonomy. The centre generates knowledge to equip engineers with design-phase solutions and in-field instruments for industry-scale systems to facilitate system’s crashless operation.