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SEIT Lab, Department of Computer Science, University of Cyprus

Tel.: [+35722892693];     Email: george@ucy.ac.cy

Human-centered AI methods, approaches, and systems • Explainable AI methods • Democratization of AI • Persuasive technologies in IUI • Privacy and security of IUI • Knowledge-based approaches to user interface design and generation • User modelling for intelligent interfaces • User-adaptive interaction and personalization • IUI for crowd computing and human computation • Human control in daily automations • Trust and reliance in intelligent systems Computational innovation • Interactive machine learning • Human-in-the loop AI testing and debugging • Human-centered recommendation and recommender systems • Generative models • Human-in-the-loop reinforcement learning • Intelligent user interfaces for generative AI Innovative User Interfaces • Affective interfaces • Intelligent aesthetic interfaces • Intelligent collaborative interfaces • Intelligent AR/VR interfaces • Intelligent visualization and visual analytics • Intelligent wearable and mobile interfaces • Intelligent tangible interfaces Intelligent Multimodal Systems • Embodied agents • Multimodal AI assistants • Intelligent multimodal interfaces Intelligent Applications • Education and learning-related technologies • Healthcare and wellbeing • Automotive • Assistive technologies • Entertainment • Workplace happiness • Social media • Internet of Things (IoT) • Smart homes Large Language Models and Agentic AI • End-user interaction with LLMs, agents, and multimodal models (e.g., chatbots, image generation) • LLMs and agents in the workplace • Human-agent interaction and multi-agent systems • Bias in LLMs and agents • The effects of LLMs and agents use on creative tasks • Personalized user interaction with LLMs and agents • Prompt engineering • User control and steering of LLMs and agents (e.g., RLHF, chaining, instruction tuning) Evaluations of Intelligent User Interfaces • User experiments and studies • Reproducibility (including benchmarks, datasets, and challenges) • Meta-analysis • Mixed-methods evaluations