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The Information and Communication Technology (ICT) research support measure is part of the IT Academy programme, which supports the strengthening of ICT research capacity and research development activities at the University of Tartu, Tallinn University of Technology and Tallinn University.
The aim of the research support measure is to increase the capacity of top-level ICT research and development in Estonia to ensure the development of Estonian science, economy and society as a whole by strengthening the implementation of knowledge-based and innovative solutions in various fields.
In every research direction, research is carried out, subject and curricula in the field are developed, and collaboration with companies, including other partners, is developed.
An advisory board has been set up for each research direction, which acts as a link between partners and ICT research stakeholders and provides recommendations to universities for the development in that line of research. The advisory boards include representatives of universities, companies and the public sector, as well as foreign researchers in their respective fields.
Artificial intelligence and machine learning are potentially one of the fastest growing areas of technology. According to predictions, this will change the functioning of both companies and countries, not to mention the construction of information systems and the field of ICT itself. While current IT technologies require a large number of highly qualified software developers to create applications, then these technologies will enable the creation of innovative software systems faster and cheaper, while also offering the possibility to create much more powerful and automated systems than previously. One of the main outputs of AI and machine learning is the creation of practical, area-specific methodologies and systems. The development of this line of research will affect both the ICT sector and other industries contributing to the higher value added services and products, as well as the wider use of automation. Among other things, one of the areas of application is the healthcare system, mainly ICT solutions for e-health and personalised medicine.
Tarun Khajuria – Junior Research Fellow of Machine Learning
Taavi Kivisik – Junior Research Fellow of Artifical Intelligenc
Viacheslav Komisarenko – Junior Research Fellow of Machine Learning
Elizaveta Korotkova – Junior Research Fellow in Natural Language Processing
Markus Kängsepp – Junior Research Fellow of Machine Learning
Maarja Pajusalu – Junior Research Fellow of Health Informatics
Novin Shahroudi – Junior Research Fellow of Machine Learning
Modar Sulaiman –Junior Research Fellow of Artificial Intelligence
Accelerated data collecting and accumulation opens up new opportunities for business development. In the conditions of a constant online presence and growing amount of information, it is important to find new methods and technological solutions that cope with and benefit from complex and voluminous data sets. In the past, data processing was used primarily to analyse past events, but now, in-depth analytics based on big data enables data analysis in real time, in addition predictive analysis and decision support based on real data are receiving increasing attention. Data science methods and big data analysis are also important in the development of the IoT, robotics, industrial automation, healthcare and many other fields, as well as in the creation of various applications, which is why strengthening this field of research is extremely important in Estonia.
Alejandra Duque Torres – Junior Research Fellow of Software Engineering
Gamal Elkoumy – Junior Research Fellow of Big Data
Rahul Goel – Junior Research Fellow in Information System
Tahira Iqbal – Junior Research Fellow of Information Systems
Samuele Langhi – Junior Research Fellow of data Managemen
Kristiina Rahkema – Junior Research Fellow of Software Engineering
The world is entering an era of robots that will ultimately improve the well-being and overall quality of life of the humankind. Robots will be taking over many tasks, which will result in, among other things, coping better with the problems arising from demographic change. It is important to increase the accessibility and application of robots to small and medium-sized companies. To increase Estonian business competitiveness, it is necessary to pay more attention to the digitalisation of industry and process management. To achieve this, it is necessary to increase the use of sensors and the Internet of Things, to make robots smarter for enabling the optimisation of the production processes, while also using process management and data analysis methodologies.
Principal Investigator for Collaborative Robotics and Robotic Computing Group of University of Tartu
Research directions: motion planning, feedback control, learning based control, optimization for robotics, planning and control under uncertainty
Farooq Ayoub Dar – Junior Research Fellow of Pervasive Computing
Mahir Gulzar – Junior Research Fellow of Autonomous Driving
Shivananda Rangappa Poojara – Junior Research Fellow of Big Data
Houman Masnavi – Junior Research Fellow in Robotics
Project activities are funded by the European Social Fund.
On 17 January at 9:00 Volodymyr Leno will defend his doctoral thesis “Robotic Process Mining: accelerating the adoption of Robotic Process