Tietotekniikan laitos


Viimeisin muutos maanantai 04. huhtikuuta 2011, 10.17
Approved by the head of the department 11.3.2011


The main strategic goal is to conduct such research in information and communication technology (ICT) that belong to some of the University’s internationally recognized significant fields or internationally outstanding areas, or belong to the University’s technology profile or technological core fields ("Excellence and Dynamism”- University of Jyväskylä 2017).

Present status

The joint themes behind all research at the department have been the methodological basics of mathematical modeling and computational methods, development of software/systems utilizing computing intensive methods, simulation based optimization, and real world development projects with industry. The main research fields are:

  • Computational Sciences
    • Scientific Computing
    • Optimization
    •  Signal Processing and Data Mining
  • Mobile Systems
  • Intelligent Systems and Software
  • Human and Educational Technology

Scientific computing supports the core field “basic natural phenomena and the structure of matter” in the University’s profile. In scientific computing and optimization main research topics have been

  • FEM based numerical simulation
  • Theory, methods and software development of multiobjective optimization (in particular interactive multiobjective optimization and decision support)
  • Applications to problems in natural sciences and engineering (e.g. acoustics and fluid dynamics).

Numerical simulation of nanoscale phenomena and fluid-structure interaction are new potential research directions.  Nanoscience, especially functional molecular nanodevices is one of the University’s internationally outstanding areas. Fluid-structure interaction is an important phenomenon in paper manufacturing technology which belongs to the University’s technology profile.

The main research topic in telecommunications is optimization of Quality of Service (QoS) in telecommunication networks. Emerging topics include control of QoS in communications networks, radio resource management & network planning, and signal processing for wireless communication. In software engineering the most important research topic has been the reliable modeling of inaccurate measurement data. Emerging fields include signal and image processing, neural computation, data-mining, methods and tools of software development process and distributed systems (multi-agent systems, peer to peer networks and semantic web). In CS teacher education the research was to be focused on education and technology in the context of Human-centered ICT being one of the University's technological core fields.


The traditional focus of the department has been in the fields that find their applications in engineering and natural sciences. The general trend to small scales and multidisciplinary models will be followed there. Simultaneously, however, more systematic approach will be needed to address large scale problems in the society using the tools of system analysis, logistics, data analysis etc combined with state of the art software engineering and wireless communication.

The Department has for a long time been proactive in extending its scope and looking for new research areas. Democratization of computing is seen to continue. This means that computationally intensive applications and sophisticated computational architectures become common place in other scientific disciplines and even in everyday environment. Thus the former “glory” of the computing as a discipline is diminished. High profile research is done only in complex multidisciplinary contexts.

To serve the community we have to provide research both for the low end (computational algorithms/applications capable to running autonomously in heterogeneous environments for daily tasks) and high end (complex multi disciplinary applications in collaboration with other teams). Assets to both directions exist. For pervasive computing the forces of signal processing/telecommunication should be combined with those of computational intelligence and evolutionary computing. For the high end the Department has good expertise in multi disciplinary optimization, reliable numerical modeling and the culture of collaborating with other disciplines inside the university. However in neither of the areas is the collaboration sufficiently focused for the time being. Moreover, the Department needs new flagship projects that profile it both in international community and in student recruitment. In addition the main thread of research should be relevant for the local/national society in relatively short time frame to secure sufficient external funding.

More specific actions supporting the main strategy are:

Research leadership and administration: Stronger leadership is needed at department level. The Department/faculty should develop university’s best environment (facilities, administration) for research projects.

Integration: The common mathematical core of the research was to be used as a resource in guaranteeing high quality of the research and improving the co-operation between different research groups. On the level of experts we need a common platform for collaboration and exchange of knowledge. Simultaneously tools have to be developed for integrating the individual research findings and software tools to new more sophisticated context aware solutions.

Publications:  Research results will be published on best international forums (international refereed journals and high level refereed conference proceedings indexed in Thomson Reuters’ ISI Web of Knowledge). The senior staff (those having PhD degree) should actively take part in research and publication related to different research groups. Each senior member of the staff should be a (co)author in 1-3 refereed papers per year on average.

Internationality: Strong emphasis is put on European co-operation. Outside Europe co-operation will be done especially with scientists and groups from USA, China, and Israel. Research periods abroad at master level, student and teacher exchange programs are encouraged. More systematic approach to FiDIPro professors and their teams is needed to exploit fully the potential collaboration. The teams and individual researchers should identify their niche expertise that could be used as an asset in international collaboration (projects and publications).

Doctoral education: The connection between research and teaching should be strengthened and the number of students and supervisors between research fields should be balanced. Recruiting potential doctoral students will be done already among third year students. They will be offered trainee positions in research projects and research oriented master studies. Doctoral students have to practice their abilities as a public performer in frequent seminars. Moreover, studies in entrepreneurship and business will be offered.  Every member of the teaching staff has to do research and every researcher has to give lectures or to supervise post graduate students. The collaboration with other disciplines (physics, psychology, sports, etc) in doctoral training is encouraged.