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ICT Research Support Measure

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.

Supported research directions developed by the University of Tartu:

  • artificial intelligence and machine learning
  • data science and big data
  • robot-human collaboration and the Internet of Things in industrial processes

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

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.

Researchers

Research directions: bioinformatics, gene expression data analysis

CV: ETIS

E-mail: raivo.kolde@ut.ee

Research directions: artificial intelligence, computational neuroscience, cognitive science

CV: ETIS

E-mail: jaan.aru@ut.ee

Research directions: music information retrieval, music generation, music emotion recognition

E-mail: anna.aljanaki@ut.ee

Research directions: deep learning, computer vision, human brain project, ethics in artificial intelligence, non-convex optimization

CV: ETIS

E-mail: kallol.roy@ut.ee

Research directions: artificial intelligence, fuzzy logic, soft computing, soft decision making

CV: ETIS

E-mail: stefania.tomasiello@ut.ee

Research directions: artificial intelligence, machine learning, deep learning, data science

CV: ETIS

E-mail: victor.pinheiro@ut.ee

Research directions: visual perception, cognitive neuroscience, human intelligence, artificial neural networks

CV: ETIS

E-mail: kadi.tulver@ut.ee

Tarun Khajuria – Junior Research Fellow of Machine Learning
E-mail: tarun.khajuria@ut.ee

Taavi Kivisik – Junior Research Fellow of Artifical Intelligenc
E-mail: taavi.kivisik@ut.ee

Viacheslav Komisarenko – Junior Research Fellow of Machine Learning
E-mail: viacheslav.komisarenko@ut.ee

Elizaveta Korotkova – Junior Research Fellow in Natural Language Processing
E-mail: elizaveta.korotkova@ut.ee

Markus Kängsepp – Junior Research Fellow of Machine Learning
E-mail: markus.kangsepp@ut.ee

Maarja Pajusalu – Junior Research Fellow of Health Informatics
E-mail: maarja.pajusalu@ut.ee 

Novin Shahroudi – Junior Research Fellow of Machine Learning
E-mail: novin.shahroudi@ut.ee

Modar Sulaiman –Junior Research Fellow of Artificial Intelligence
E-mail: modar.sulaiman@ut.ee

Advisory Board

  • Samuel Kaski (Aalto University)
  • Simo Särkkä (Aalto University)
  • Tanel Tammet (Tallinn University of Technology)
  • Priit Palumaa (Mooncascade)
  • Deniss Ojastu (Helmes)
  • Ott Velsberg (Ministry of Economic Affairs and Communications)
  • Karl H. Peterson (Estonian Health Insurance)

Data Science and Big Data

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.

Research directions: software craftsmanship, frameworks for the Internet of Things (IoT), virtual reality work and teaching environments

CV: ETIS

E-mail: ulrich.norbisrath@ut.ee

Research directions: human-centric information systems, e-government services, emotional chatbots, ontologies, multi-agent systems

CVETIS

E-mail: kuldar.taveter@ut.ee

Research directions: secure computation

CV: ETIS

E-mail: toomas.krips@ut.ee

Research directions: big data management, cloud computing, IoT, high-performance data analytics, data privacy and security

CV: ETIS

E-mail: feras.awaysheh@ut.ee

Research directions: security engineering, applied cryptography, system security

CV: ETIS

E-mail: arnis.parsovs@ut.ee

 

Research directions: software reverse engineering and software security

CV: ETIS

E-mail: denizalp.kapisiz@ut.ee

Alejandra Duque Torres – Junior Research Fellow of Software Engineering
E-mail: alejandra.duque.torres@ut.ee

Gamal Elkoumy – Junior Research Fellow of Big Data
E-mail: gamal.elkoumy@ut.ee

Rahul Goel – Junior Research Fellow in Information System
E-mail: rahul.goel@ut.ee

Tahira Iqbal – Junior Research Fellow of Information Systems
E-mail: tahira.iqbal@ut.ee

Samuele Langhi – Junior Research Fellow of data Managemen
E-mail: samuele.langhi@ut.ee

Kristiina Rahkema – Junior Research Fellow of Software Engineering
E-mail: kristiina.rahkema@ut.ee

Advisory Board

  • Torben Bach Pedersen (Aalborg University)
  • Innar Liiv (Tallinn University of Technology)
  • Dan Bogdanov (Cybernetica)
  • Agu Leinfeld (Datel)
  • Mart Mägi (Statistics Estonia)

Robot-human collaboration and the Internet of Things in industrial processes

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.

Researchers

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

CV: ETIS

E-mail: arun.singh@ut.ee

Principal Investigator for Distributed and Pervasive Systems Group of University of Tartu

Research directions: pervasive computing, mobile computing, pervasive data science, explainable AI, unmanned autonomous vehicles

CV: ETIS

E-mail: huber.flores@ut.ee

Research directions: edge intelligence, distributed and pervasive sensing, underwater micro-clouds

CV: ETIS

E-mail: mohan.liyanage@ut.ee

Research directions: behaviour modeling and prediction, autonomous navigation, robotics

CV: ETIS

E-post: naveed.muhammad@ut.ee

Research directions: human mobility, network science, probabilistic methods, algorithms, optimization

CV: ETIS

E-mail: mozhgan.pourmoradnasseri@ut.ee

Research directions: mobility modelling, network algorithms, computer simulation, probabilistic methods

CV: ETIS

E-mail: kaveh.khoshkhah@ut.ee

Research directions: workflow-based Internet of Things, mobility-aware computing, data integration in smart cities

CV: ETIS

E-mail: jakob.mass@ut.ee

Farooq Ayoub Dar – Junior Research Fellow of Pervasive Computing
E-mail: farooq.ayoub.dar@ut.ee

Mahir Gulzar – Junior Research Fellow of Autonomous Driving
E-mail: mahir.gulzar@ut.ee

Shivananda Rangappa Poojara – Junior Research Fellow of Big Data
E-mail: shivananda.poojara@ut.ee

Houman Masnavi – Junior Research Fellow in Robotics
E-mail: houman.masnavi@ut.ee

Advisory Board

  • Petteri Nurmi (University of Helsinki)
  • Alar Kuusik (Tallinn University of Technology)
  • Kuldar Väärsi (Milrem)
  • Aivar Avalo (Eesti Energia)
  • Kaupo Reede (Ministry of Economic Affairs and Communications)
  • Lauri Kuusisto (ABB)

Supported research directions developed by Tallinn University of Technology:

  • software reliability
  • the Internet of Smart Things
  • hardware and system security and reliability

Supported research directions developed by Tallinn University:

  • digital transformation and lifelong learning

 

Project activities are funded by the European Social Fund.

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04.01.2022
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22.11.2021