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Obtaining statistical data

Projects / Programmes source: ARIS

Artificial Intelligence and Intelligent Systems

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Periods
January 1, 2022 - December 31, 2027
Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   

Code Science Field
1.02  Natural Sciences  Computer and information sciences 
Keywords
artificial intelligence, machine learning, deep learning, data mining, data integration, qualitative modelling, intelligent robotics, evolutionary computation, heuristic search, intelligent tutoring systems, automatic commenting, multiagent systems, ambiental intelligence, explanation
Evaluation (rules)
source: COBISS
Points
15,359.27
A''
1,886
A'
5,412.23
A1/2
7,336.89
CI10
32,979
CImax
8,099
h10
67
A1
49.3
A3
49.25
Data for the last 5 years (citations for the last 10 years) on September 21, 2023; A3 for period 2017-2021
Data for ARIS tenders ( 04.04.2019 – Programme tender , archive )
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Database Linked records Citations Pure citations Average pure citations
WoS  772  29,474  28,162  36.48 
Scopus  1,041  40,503  38,503  36.99 
Researchers (53)
no. Code Name and surname Research area Role Period No. of publications
1.  52211  Andrejaana Andova  Engineering sciences and technologies  Junior researcher  2022 - 2023  19 
2.  57743  Simon Bele    Technical associate  2022  0 
3.  28779  PhD Zoran Bosnić  Engineering sciences and technologies  Researcher  2022 - 2023  210 
4.  02275  PhD Ivan Bratko  Engineering sciences and technologies  Researcher  2022 - 2023  740 
5.  23399  PhD Tomaž Curk  Engineering sciences and technologies  Researcher  2022 - 2023  243 
6.  53247  PhD Carlo Maria De Masi  Engineering sciences and technologies  Researcher  2022 - 2023  18 
7.  16324  PhD Janez Demšar  Engineering sciences and technologies  Researcher  2022 - 2023  340 
8.  31049  PhD Erik Dovgan  Engineering sciences and technologies  Researcher  2022  140 
9.  32930  Aleš Erjavec    Technical associate  2022 - 2023  12 
10.  29485  PhD Jana Faganeli Pucer  Engineering sciences and technologies  Researcher  2022 - 2023  32 
11.  05026  PhD Bogdan Filipič  Engineering sciences and technologies  Researcher  2022 - 2023  470 
12.  08501  PhD Matjaž Gams  Engineering sciences and technologies  Researcher  2022 - 2023  1,649 
13.  30915  PhD Dejan Georgiev  Medical sciences  Researcher  2022 - 2023  186 
14.  29523  PhD Anton Gradišek  Natural sciences and mathematics  Researcher  2022 - 2023  414 
15.  33187  PhD Vida Groznik  Engineering sciences and technologies  Researcher  2022 - 2023  58 
16.  35424  PhD Tomaž Hočevar  Engineering sciences and technologies  Researcher  2022 - 2023  27 
17.  38246  PhD Vito Janko  Engineering sciences and technologies  Researcher  2022 - 2023  63 
18.  55783  Emilija Kizhevska  Engineering sciences and technologies  Junior researcher  2022 - 2023  4 
19.  54043  Primož Kocuvan    Technical associate  2022 - 2023  19 
20.  55755  Jaka Kokošar  Engineering sciences and technologies  Junior researcher  2022 - 2023  0 
21.  55599  Žiga Kolar    Technical associate  2022 - 2023  5 
22.  52047  Tine Kolenik  Engineering sciences and technologies  Junior researcher  2022 - 2023  45 
23.  04242  PhD Igor Kononenko  Engineering sciences and technologies  Researcher  2022 - 2023  475 
24.  32317  PhD Jana Krivec  Social sciences  Researcher  2022 - 2023  119 
25.  14565  PhD Matjaž Kukar  Engineering sciences and technologies  Researcher  2022 - 2023  215 
26.  23581  PhD Mitja Luštrek  Engineering sciences and technologies  Researcher  2022 - 2023  461 
27.  52097  Teodora Matić  Engineering sciences and technologies  Junior researcher  2022 - 2023  5 
28.  32926  PhD Miha Mlakar  Engineering sciences and technologies  Researcher  2022  53 
29.  29021  PhD Martin Možina  Engineering sciences and technologies  Researcher  2022 - 2023  76 
30.  52096  Amra Omanović  Engineering sciences and technologies  Junior researcher  2022 - 2023  8 
31.  57702  Neža Pajek Arambašič  Engineering sciences and technologies  Researcher  2023  0 
32.  19365  PhD Matjaž Pančur  Engineering sciences and technologies  Researcher  2022 - 2023  91 
33.  53630  Aleš Papič  Engineering sciences and technologies  Junior researcher  2022 - 2023  0 
34.  57109  Ela Praznik  Engineering sciences and technologies  Researcher  2022  0 
35.  50956  Nina Reščič  Engineering sciences and technologies  Technical associate  2022 - 2023  38 
36.  20389  PhD Aleksander Sadikov  Engineering sciences and technologies  Researcher  2022 - 2023  183 
37.  50929  Gašper Slapničar  Engineering sciences and technologies  Junior researcher  2022 - 2023  37 
38.  51054  Maj Smerkol    Technical associate  2022 - 2023  12 
39.  54708  David Susič  Engineering sciences and technologies  Junior researcher  2022 - 2023  23 
40.  15656  PhD Tomaž Šef  Engineering sciences and technologies  Researcher  2022 - 2023  390 
41.  31917  PhD Domen Šoberl  Engineering sciences and technologies  Researcher  2022 - 2023  36 
42.  57111  Martin Špendl  Engineering sciences and technologies  Researcher  2022 - 2023  4 
43.  32318  PhD Aleš Tavčar  Engineering sciences and technologies  Researcher  2022 - 2023  93 
44.  30142  PhD Marko Toplak  Engineering sciences and technologies  Researcher  2022 - 2023  27 
45.  24894  PhD Tea Tušar  Engineering sciences and technologies  Researcher  2022 - 2023  202 
46.  52212  Jakob Valič    Technical associate  2022 - 2023  11 
47.  37486  PhD Anita Valmarska  Engineering sciences and technologies  Researcher  2022  26 
48.  39266  Aljoša Vodopija  Engineering sciences and technologies  Junior researcher  2022  50 
49.  31563  PhD Petar Vračar  Engineering sciences and technologies  Researcher  2022 - 2023  30 
50.  54820  Marko Zeman  Engineering sciences and technologies  Junior researcher  2022 - 2023  6 
51.  12536  PhD Blaž Zupan  Engineering sciences and technologies  Head  2022 - 2023  524 
52.  29020  PhD Jure Žabkar  Engineering sciences and technologies  Researcher  2022 - 2023  115 
53.  30921  PhD Lan Žagar  Engineering sciences and technologies  Researcher  2022 - 2023  17 
Organisations (2)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  86,973 
2.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  14,778 
Abstract
In our fast-changing world, one of the technologies sticks out. The technology that will change our daily routines, change the way we learn, how we work, how we buy goods, how we spend our free time, how we commute, the way we find friends and communicate, and the way we reach out to the stars. The technology that will change everything. Artificial intelligence. We, a group of fifty researchers, innovators, and educators, are proposing to continue to explore new ways, methods, and algorithms that build up artificial intelligence. In the past, we have already invented techniques and tools that have contributed to its growth and that the scientists have recognized as its key components. We created ways to make artificial intelligence and its models easier to understand, ways to explain its predictions, and means to integrate large volumes of heterogeneous data. We embedded these methods into tools and offered them to the community of scientists, researchers, and educators. We enriched local industry with our knowledge of data-driven management and production, devised applications to help some of the most prominent Slovenian industries to grow and keep the comparative advantage, and collaborated with startups to define their cutting-edge technologies. We have collaborated with hospitals and clinical centers to improve the health care system and clinical treatments, devised means for the assisted living of the elderly, and contributed to advancements in other research fields, such as molecular biology and ecology. We will continue to develop, innovate, disseminate, collaborate, and educate. We are here proposing a continuation of our Programme. In developing new methods and tools, we still focus on explainability, interpretation, use of domain knowledge, visual presentation of data, models, and discovered patterns, engagement of domain experts, and data fusion. These areas have formed the foundation of our research in the past and have recently become the hottest research topics with the omnipresence of AI and the success of deep neural networks. We propose to structure our work to address the development of AI methods, applications, tools, and education. We will innovate data mining and visualization, deep learning, recommender systems, argument-based learning, qualitative modeling, evolutionary computation and heuristic search, and agent-based learning. In all these approaches, we will specifically address explanation, interpretation, and, where applicable, fairness of derived models. We will collaborate with industry, healthcare providers, and the public sector to apply AI and deliver cutting-edge technology to our community. We will continue to make some of the world's best software tools for AI and continue to impress our peers with their utility and robustness. And finally, we plan further to develop our approach to conceptual training of AI, and promote its deliverance to schools, universities, industry, and community.
Significance for science
We propose to research several crucial and timely topics in artificial intelligence that are very important due to the impact and applicability of this fast-developing area of science. The programme will significantly contribute to the development of new methods that address these topics, create practical and useful software environments that support both research and utility of these methods, and confirm the applicability of our new scientific results in practice. We will continue to address the problems of explainability and interpretation of AI models and the inclusion of humans in the model development loop. The creation of transparent and human-readable models that can include available domain knowledge has been a determining trait of our programme since its beginnings. We have already contributed world-renowned techniques to address these problems in feature scoring, model explanation, and data fusion approaches. The recent emergence and popularity of deep models, the availability of large data sets, and surge of AI applications in all, including sensitive, areas of life have exposed the need for explainability, interpretability and faithfulness. We are pleased that we have a head start in this area of research and can continue to make significant contributions in the future. Our proposed research addresses disciplines beyond computer science. The AI methods, including machine learning, data mining, exploration of domain knowledge, data fusion, search and optimization, and design of intelligent systems, became vital for the infrastructure of other scientific disciplines, both in natural and social sciences. Today, AI impacts all the fields where data abounds, and with digitalization, AI is becoming omnipresent. The programme addresses these other disciplines through applied research and collaborations with partner institutions. Our mission is to develop AI approaches to contribute to the development of science, and our duty to use it wisely and educate about its reach and impact.
Significance for the country
Digitalization and its upgrade with AI have recently been set as top priorities in the technological development of the EU and Slovenia. Public administration in Slovenia has recently crafted a "National Program to Promote the Development and Use of AI until 2025" (NpAI), which is now being signed by the Slovene Government. Our programme proposes actions that will contribute to education, training, transfer of knowledge, and implementation of AI techniques both in industries and the public sector. Our proposed programme is well-aligned with recent developmental initiatives, including NpAI. We have and will continue to design AI approaches that can advance our industrial partners. We will continue to collaborate with major industries and SMEs in the country, including industries in steel and appliance manufacturing, pharmacy, retail, and automatization (see Section 32). We have creative collaboration with selected SMEs that can place our products and services on the market. And we will strive to innovate in developing end-user AI software, including our flagship data mining toolbox Orange. An important part of our programme addresses emerging needs in healthcare and assisted living. AI is a crucial component of emerging healthcare tools, thus helping healthcare systems cope with the aging population and increasing chronic patients. It also demonstrated that it could assist in emergencies such as the recent COVID-19 pandemic. Personal health systems are an affordable way of bringing quality healthcare to a broad population, improving equality of access to health services. Assisted living systems powered by AI can help seniors age in place, preserving their quality of life and contributing to the sustainability of social care systems. The research programme - in collaboration with domain experts from various fields, such as molecular biologists and clinical experts - will contribute by developing medical data analysis methods, devices and methods for assisted living, tools for personalized medicine, and by searching for novel biomarkers and diagnostic/screening methods based on emerging sensor technologies (e.g. eye-tracking, wearables, etc.). We build on our long-term collaboration with medical professionals; some of these collaborations even predate this programme (est. in 1999). AI can enhance cultural experiences. While this is not a major direction of our research, the programme has contributed to providing access to digitized and physical cultural heritage for citizens and tourists in the past. We will be on the lookout for opportunities to do so again. We also closely collaborate with several public administration institutions, including the Ministry of Public Administration and Ministry of Agriculture, Forestry and Food. This collaboration aims to advance their digital infrastructures and seek opportunities where AI implementation would improve the quality of their services and support decision-making. We offer hands-on courses designed for public administration employees and have carried out about ten workshops that showcased the use of machine learning. We aim to continue with such training and carry on with pilot projects that demonstrate the use of AI in the public sector. At present, our collaboration with the Ministry of Public Administration in the development of semantic analysis of documents has been recognized as a flagship R&D project in the public sector that uses AI. Many members of the programme group are university teachers. With the importance of the AI methods and their great potential socioeconomic influence, it is essential to teach these methods and their practical use to new generations of students. Our strong collaborations with foreign partners will additionally enrich socioeconomic impact. The group established relations with numerous prestigious foreign institutions and brought several foreign scientists on shorter and longer visits to Slovenia. We also plan to involve them in teaching at the University of Ljubljana and Jožef Stefan Institute.
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