Projects / Programmes source: ARRS

Complex networks

January 1, 2013 - December 31, 2016
Research activity

Code Science Field Subfield
1.07.01  Natural sciences and mathematics  Computer intensive methods and applications  Algorithms 
1.01.05  Natural sciences and mathematics  Mathematics  Graph theory 

Code Science Field
P170  Natural sciences and mathematics  Computer science, numerical analysis, systems, control 

Code Science Field
1.01  Natural Sciences  Mathematics 
Evaluation (rules)
source: COBISS
Researchers (23)
no. Code Name and surname Research area Role Period No. of publications
1.  36412  PhD Vesna Andova  Mathematics  Researcher  2013 - 2016  40 
2.  36664  PhD Kristina Ban  Computer intensive methods and applications  Junior researcher  2013 - 2016 
3.  24708  PhD Nadja Damij  Economics  Researcher  2013 - 2016  192 
4.  35875  MSc Marjeta Grahek    Technician  2016 
5.  38085  PhD Petr Gregor  Mathematics  Researcher  2015 - 2016  40 
6.  26484  PhD Andrej Kastrin  Medical sciences  Researcher  2013 - 2016  125 
7.  33510  PhD Jelena Klisara  Mathematics  Technician  2013 - 2016  14 
8.  36238  PhD Martin Knor  Mathematics  Researcher  2013 - 2016  115 
9.  36666  Jaka Kranjc  Mathematics  Junior researcher  2013 - 2016 
10.  27800  PhD Zoran Levnajić  Physics  Researcher  2013 - 2016  123 
11.  32319  Nataša Lisec    Technician  2013 - 2016 
12.  31670  PhD Borut Lužar  Computer intensive methods and applications    2013 - 2016  175 
13.  24404  PhD Matej Mertik  Computer science and informatics  Researcher  2013 - 2015  114 
14.  36836  PhD Biljana Mileva Boshkoska  Computer science and informatics  Researcher  2016  146 
15.  30048  PhD Uroš Pinterič  Political science  Researcher  2013 - 2015  264 
16.  38768  PhD Boris Podobnik  Information science and librarianship  Researcher  2016  105 
17.  22649  PhD Janez Povh  Computer intensive methods and applications  Researcher  2013 - 2016  323 
18.  34728  PhD Nataša Pržulj  Computer science and informatics  Researcher  2013 - 2016  95 
19.  20934  PhD Blaž Rodič  Administrative and organisational sciences  Researcher  2013 - 2016  189 
20.  20076  PhD Borut Rončević  Interdisciplinary research  Researcher  2015 - 2016  337 
21.  36239  PhD Roman Sotak  Mathematics  Researcher  2013 - 2016  60 
22.  15518  PhD Riste Škrekovski  Mathematics  Principal Researcher  2013 - 2016  497 
23.  23904  PhD Aleksandra Tepeh  Mathematics  Researcher  2014 - 2016  129 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  2784  Faculty of Information Studies in Novo mesto  Novo mesto  3375650  4,113 
Science of complex networks studies the mechanisms of emergence of collective phenomena through self-organization in systems composed of many interacting entities such as genes, ants or persons. Triggered by empirical discoveries of universal properties in real-world networks, this expanding field displays a 10-fold increase in publications over the last decade. By combining graph theory with experimental insights into real complex systems such as society or the Internet, this young interdisciplinary science contributed fundamental results, ranging from understanding of the genetic systems to improving infrastructure networks. Slovenian science however, despite its recognized excellence in a variety of disciplines, is still short of the adequate response to swift growth of this field.   We hereby propose the research Program “Complex Networks” aimed at putting our country at the forefront of this challenging scientific area. Our Program envisages five directions: (i) development of novel methods of reconstructing the structure and predicting links in real networks based on the empirical data; (ii) detecting the properties of biological networks responsible for their superb functionality and manufacturing bio-inspired methods of network design; (iii) defining a unique identification of network complexity by completing presently used set of indices that quantify network structure; (iv) analytical and numerical extensions of classical graph optimization problems to large real-world networks; (v) construction of novel models of evolving social networks through bio-inspired paradigms such as ant colonies and evolutionary algorithms. Our work will be carried out by interdisciplinary research group employing an array of methodologies: computationally intensive modeling and simulations involving both general-purpose languages and high-level software, machine learning, techniques from optimization and graph theory, and eventually experimental testing.   Our findings are expected to establish a new state-of-the-art in the field by contributing results along currently investigated as well as the original research lines, potentially sparking novel research routes. By pursuing interdisciplinary work and organizing scientific events, we intend to develop and strengthen collaborations worldwide. Technologically implementable findings, of potential interest to industries such as biotechnology, pharmacy, telecommunications or urban transportation will be emphasized. Developed computational methods will be formulated as opensource software freely available for the scientific community. Long-term results of our work are likely to have impact on Slovenia in many constructive ways, primarily through their relation to life, social and behavioral sciences. Intense exchange of young scientists will be a key part of our work, thus not only enhancing scientific thought in our country, but also improving the circulation of ideas in and out of Slovenia.
Significance for science
The number of scientific papers whose titles contain the expression "complex network", grew from 147 in the year 2001, to 2500 in the year 2015. This trend suggests that complex networks are likely to remain a vibrant and dynamic field whose growth will continue beyond the present time. The choice of our research directions includes topics of intense ongoing work such as network reconstruction and network design, together with novel topics in their infancy, such as the introduction of additional graph indices that identify network's complexity. This indicates that our research plan is well timed and is making a significant contribution to the field. Our research group is comprised of members with scientific backgrounds ranging from mathematics, computer science and computational statistics to physics, biology and neuroscience, hence our choice of interdisciplinary research direction is adequate. Through numerous collaborations, our work improves scientific communication among researchers with very diverse backgrounds, and thus enhances interconnections within the complex networks scientific community at the international level. It is also worth mentioning that the interdisciplinarity of the field is growing, since more and more disciplines are finding complex networks methods and models useful. Our research is novel also in the context of the involved methodology. We developed software packages for analyzing and quantifying properties of complex networks, that employ intensive computing, and that we are continuously developing in parallel with the progress of our research. We will make these tools available to research community. Finally, our findings are likely igniting new research avenues. Novel methods of network reconstruction may reveal characteristics of biological networks responsible for their optimality, which could open a new chapter in bioinspired technology. New insights into functioning of biological networks themselves, obtained through experimental data, could become useful in detecting or even preventing various diseases. Richer and more detailed models of social networks may turn a new page in modern sociology providing social scientists with tools for obtaining more quantitative insights into topics of their work. Understanding dynamics and evolution of social network is also relevant for medical issues, such as design of vaccination campaigns. Measuring and parametrizing the complexity of network structure can easily become an indispensable tool in network analysis, allowing a new classification of realworld networks, outdating current frameworks of 'scalefree' and 'smallworld' models.
Significance for the country
Study of complex networks is automatically a study of real world--in fact, society is nothing but a network of individuals. It is therefore only natural to expect that our scientific efforts are connected to current social and economics needs. In particular, outputs of our work benefit several economic sectors, including high-tech industries such as biotechnology, pharmacy or communications, where the Slovenian industry has a long and successful history. Computational social science results might be of interest to policy makers and wider public, as they will grasp intricate social phenomena that help us understand our society’s dynamics. Except on purely scientific front, our long-term results will benefit Slovenia in several other ways. By pursuing interdisciplinary work and organizing scientific events, we intend to strengthen collaborations worldwide, which at present include Oxford University, Harvard University, Imperial College London, UCL, Boston University, University of California Santa Barbara, National University of Singapore, East Chine University of Science, Tokyo University, and most of the main Universities in Czech Republic, France, Croatia and Slovakia. Exchange of young scientists is a key part of our work, not only enhancing scientific thought in our country, but also improving the circulation of ideas in and out of Slovenia. This can create initiatives for new EU project and bring funding into the country. In fact, in 2016, we organized eigth ITIS conference, annual international meeting where computational and social sciences meet. We have been active in the past as well, organizing Researchers' Night – general presentation of scientific activities through workshops, public lectures and “open doors” of laboratories. This can in turn improve Slovenia's education system through bringing new educational potential into the country. Due to its interdisciplinarity, our work is likely to influence other scientific disciplines of Slovenian science, many of which are already highly recognized worldwide. The organization of scientific meetings and conferences will improve interconnections among Slovenian scientists, as well as their collaborations with international scientific centers. We are successfully engaged in curating Top Publications ("TOPobjave") section at Slovenia's online portal Metina lista, where we offer a monthly summary of best scientific achievements by the Slovenian scientists, explained at the popular non-technical level. Our experience in this indicates that while Slovenian science is clearly following the cutting-edge international trends, public awareness of this is poor or often even distorted. For this reason we are decisive to put a very strong emphasis of disseminating our own and generally Slovenian research results in local and national media. This will not only enrich Slovenian scientific culture but also Slovenian language, where translating the scientific terms, particularly new ones, is imperative.
Most important scientific results Annual report 2013, 2014, final report
Most important socioeconomically and culturally relevant results Annual report 2013, 2014, 2015, final report
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