Human-centered Computing Group
The Human-centered Computing group works in the interdisciplinary areas of Human-Computer Interaction, Human-centered User Modelling, Adaptive User Interfaces, and Human Cognition and Emotions. HCC is investigating the influence of human cognitive and emotional aspects in interactive systems aiming to drive the design and development of adaptive and personalized solutions to the unique characteristics of the end-users. The lab works on three main research directions: i) Human Factors Research: Investigating the influence of human cognitive and emotional factors in a variety of application domains (usable security, e-commerce, e-learning); ii) User Modeling Research: Design and development of innovative user modeling mechanisms that leverage on knowledge inferred from smart wearable, eye-tracking and holographic devices; and iii) Personalization Research: Design and development of innovative human-centered adaptive interactive systems for improving user experiences and performance in various settings such as desktop, mobile, wearable and mixed/augmented reality.
Selected Publications
Constantinides, A., Belk, M., Fidas, C., Samaras, G. (2018) "On cultural-centered graphical passwords: Leveraging on users’ cultural experiences for improving password memorability" ACM SIGCHI User Modeling, Adaptation and Personalization (UMAP 2018), ACM Press, 245-249
Katsini, C., Fidas, C., Raptis, G., Belk, M., Samaras, G., Avouris, N. (2018) "Influences of human cognition and visual behavior on password security during picture password composition" ACM SIGCHI Human Factors in Computing Systems (CHI 2018), ACM Press, article number 87
Katsini, C., Fidas, C., Raptis, G., Belk, M., Samaras, G., Avouris, N. (2018) "Eye gaze-driven prediction of cognitive differences during graphical password composition" ACM SIGCHI Intelligent User Interfaces (IUI 2018), ACM Press, 147-152
Raptis, G., Katsini, C., Belk, M., Fidas, C., Samaras, G., Avouris, N. (2017) "Using Eye Gaze Data and Visual Activities to Infer Human Cognitive Styles: Method and Feasibility Studies" In Proceedings of the ACM conference on User Modeling, Adaptation and Personalization (UMAP’17), ACM Press, 164-173