This research area focuses on the development of advanced systems in which artificial intelligence plays an active role in interaction with users, the environment, and digital content. The emphasis is on integrating computer vision, speech processing, generative models, and adaptive algorithms into unified, responsive systems capable of contextual understanding and real-time decision-making.
Research explores methods for perception and interpretation of the environment (segmentation, object recognition, emotion detection, and user intent analysis), as well as situation-aware content generation — from visual elements and speech to the behavior of virtual agents. Special attention is given to systems that learn through interaction, adapt to individual users, and continuously improve through feedback.
Applications include intelligent educational systems, adaptive video games, assistive technologies, augmented and virtual reality, and multimodal AI agents that combine vision, language, and action. The goal is to develop robust, scalable, and ethically responsible systems that enable natural and effective collaboration between humans and artificial intelligence in both real and virtual environments.
Technologies Used
- Multimodal artificial intelligence (vision + speech + language)
- Computer vision and scene segmentation
- Emotion and user behavior recognition
- Generative models (image, speech, text)
- Large language and vision-language models
- Human–computer interaction (HCI)
- Adaptive and self-learning systems
- AI in games, XR, and assistive technologies
