The DigiWorld Priority Research Area covers research related to the digital turn: the development of digital technologies and the ensuing social changes, large sets of digitised data and the AI methods that enable their processing, analysis and modelling. It is an area of visionary basic research, interdisciplinary applications, and the development of digital technologies that requires ambitious collaboration between different fields: exact sciences, humanities, social sciences, and natural sciences.
The activities of the DigiWorld PRA will focus on four research domains:
1. Advanced computing and Artificial Intelligence
This domain comprises both basic and applied research, leading to the creation and development of new computational methods adapted to different types of data, including, but not limited to, non-standard types of machine learning (e.g. semi-supervised, multi-task, multimodal ML); non-linear source separation; advanced ML optimisation methods; ML on small data sets; explainable AI; designing neural networks based on biological networks, construction of neuromorphic systems; quantum algorithms and quantum cyber-security; image, speech, data stream analysis, etc.
2. Digital transformation of the society and the economy
This domain comprises research problems concerning the digital transformation and the life of the individual and society in the digital world, including, but not limited to: human-machine interfaces, brain-computer interfaces, affective computing; the psychological effects of digitisation, as well as the use of AI tools in the analysis of psychological experiments; ethics, law and policies related to the development, implementation and application of information and communication technologies (e.g. autonomous machines) as well as ML-supported legal decision-making processes or the computational social choice theory; cyber-security (cyberspace securitisation, dehumanisation of the battlefield); digital economy and the macroeconomic and financial risks in the digital world (including the use of neural networks for analysing data from financial and foreign exchange markets, etc.); the impact of the latest technologies on media and social communication (including their quantitative analysis, e.g. to develop strategies of combatting fake news).
3. Digital Humanities
This domain includes, but is not limited to: digital research on language, literature, culture and the arts: quantitative and qualitative analysis of textual and multimedia data, the use of computational methods (ML, information retrieval, text mining, natural language processing) in literary, linguistic and cultural research (e.g. stylometry, computational linguistics, including corpus linguistics, machine translation studies, etc.), and the use of mathematical methods (e.g. machine learning, information retrieval, text mining, natural language processing); digital cultural heritage archives (text, image, sound, video, maps, 3D models): the production and maintenance of digital resources, including digitisation of text and multimedia, architectural and archaeological scanning, etc.; the individual, culture, art and society in the digital world: the impact of digitisation on social and cultural life, communication/cultural texts in the digital world (e.g. computer games, new media, electronic literature), digital tools and methods in teaching and translation.
4. AI in exact and natural sciences
This domain comprises the application and adaptation of various AI methods to large data sets in specific research problems in exact and natural sciences, including, but not limited to: the processing and analysis of macro- and microscopic space mission images, the creation and interpretation of digital terrain models; processing social, economic, geographic and other spatial data (satellite, airborne, laser scanning, etc.) to model the complex human-environment system; analysing medical and biological images; modelling complex molecular system formations, predicting the structures of new chemical compounds, bioactive substances, etc.; optimisation of elementary particle detection in LHC experiments.
PRA Cordinator: dr hab. Jakub Gizbert-Studnicki, Faculty of Physics, Astronomy and Applied Computer Science
PRA assistant in the ID.UJ Office: Bartłomiej Konecko, e-mail: firstname.lastname@example.org, phone: 12 663 30 21