HICUP Lab Center
printHICUP - Humans Interacting with Computers Lab at the University of Primorska
Website: https://hicup.famnit.upr.si/
Vision
Our ability to process, collect, generate and transmit data has substantially increased in the recent time. This new digital world of information and knowledge is becoming the new medium for human evolution where our physical, intellectual and social abilities can develop at new speed.
However, when we try to augment our human abilities by using this digital wealth of information and knowledge we are confronted with a user interface which presents itself as the bottleneck between us humans and this digital resource. Autonomous agents are gaining a superior position over humans because their methods for using this digital resource progress faster than user interfaces. To enable digital augmentation of human abilities to its fullest potential we need to unclog this bottleneck between us humans and computers and make the digital world fit for humans.
We are trying to achieve this by exploring novel interaction concepts, advancing sensing methods and finding new ways of improving personalized services through the usage of psychological models in personalisation algorithms. We leverage on techniques such as: data mining, machine learning, computer vision, computer graphics and human perception and cognition.
Infrastructure
There are three laboratories within the center: the Laboratory for Immersion Analytics, the Laboratory for the Study of Cognitive, Perceptual and Behavioral Processes, and a Design Studio.
Immersive Analytics Lab
Immersive Analytics (IA) is an interdisciplinary research area that focuses on exploring novel interaction techniques for analyzing data. The interaction with data facilitates analytical reasoning, particularly important when one wants to enhance people's ability to individually or collaboratively analyze and explore large datasets in order to:(i) discover new tacit and explicit knowledge, (ii) transfer such knowledge by supporting learning or teaching, (iii) perform decision making, especially in situations that require resolving complex and time critical problems, and (iv) carry out control or monitoring of future systems that employ artificial intelligence. This is particularly the case when one has a large amount of data. Such is the case in Innorenew where smart materials that will build our future environments also act as data collectors producing vast quantities of data. The challenge here is how to utilize this data in the best possible way. One possibility is to use IA data exploration techniques and tools which would be developed and advanced here. In addition, these immersive technologies (an integral part of immersive analytics) also enable one to immerse data into living environments and enable research on how people interact with such physical spaces and collaborate within them, which is also an important part of Innorenew project.
Člani centra HICUP Lab
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Assoc. Prof. Matjaž Kljun, PhD Head of the Center Research area: human-computer interaction, personal information management, augmented reality, virtual reality, ubiquitous computing |
Assist. Prof. Klen Čopič Pucihar, PhD Cohead of the Center Research area: human-computer interaction, personal information management, augmented reality, virtual reality, ubiquitous computing |
Assoc. Prof. Prof. dr. Marko Tkalčič, PhD Cohead of the Center Research area: psychology-driven personalization, recommender systems, user modeling |
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Assist. Prof. Vida Groznik, PhD Researcher and Assistant Professor Research area: Artificial Intelligence, Medical Informatics |
Researcher and assistant Domen Šoberl, PhD Research area: Artificial Intelligence, Machine Learning |
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Maheshya Weerasinghe Doctoral Student Research area: Human-computer Interaction, E-learning, Augmented & Virtual Reality |
Cuauhtli Campos Doctoral Student Research area: Human-Computer Interaction, Game Thinking, Interaction Design |
Nuwan T Attygalle Doctoral Student Research area: Human-computer Interaction, Machine Learning |
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Jordan Aiko Deja Doctoral Student Research area: Human-computer Interaction, Computational Interaction, Music Learning |
Elham Motamedi Doctoral Student Research area: Complex Networks, Machine learning, Recommender systems |