ACTIVE RESEARCH DIRECTIONS

My research examines how intelligent systems behave once they leave controlled environments and enter the real world; where uncertainty, human variability, and contextual complexity dominate. I am interested in building computational models that remain robust, interpretable, and adaptable when deployed in settings that involve people, physical spaces, and social dynamics.

My current research agenda is organized around three tightly connected themes, approached from complementary system-level, algorithmic, and applied perspectives.

Human–Centered Intelligent Systems

I investigate how intelligent systems can be designed to remain transparent, controllable, and aligned with human goals under real-world constraints. This includes developing interaction and control paradigms that keep humans meaningfully in the loop within complex cyber-physical-social systems, where algorithmic decisions interact with physical processes and social dynamics.

User Modeling and Personalization

I explore algorithmic strategies for constructing adaptive user models from multimodal sensing data, interaction logs, behavioral dynamics, and cognitive signals. Rather than treating users as static profiles, I design these models as evolving computational representations that continuously update over time, enabling robust personalization and recommendation mechanisms that remain aligned with the changing behavior, goals, and contexts of human users across domains.

My current focus as a primary applied research direction is the development of AI-enabled art therapy systems that combine multimodal user modeling, affective and behavioral signals, and interaction data to support adaptive and personalized therapeutic experiences aligned with clinical practice. In parallel, I explore immersive and spatial technologies, including VR, AR, and XR, to extend art therapy into remote and hybrid settings, using presence and spatial interaction to create new possibilities for digital therapeutic intervention.

Digital Therapeutic Technologies

RESEARCH LANDSCAPE

My research has been supported through competitive national and European funding schemes, and long-term international collaborations with academic, industrial, and public-sector partners.

__________________________________

Projects & Research Collaborations

I have contributed to and led research initiatives supported by European and international funding programs, in collaboration with academic, clinical, and industry partners.

CrossCult

The European "CrossCult": Empowering reuse of digital cultural heritage in context-aware crosscuts of European history" project aims to spur a change in the way European citizens appraise History.

Brainsourcing for Affective Attention Estimation

Attention estimation and annotation are tasks aimed at revealing which parts of some content are likely to draw the users’ interest.

Context-aware adaptive visualizations for critical decision making

SYMBIOTIK

CoachAI

CoachAI is a conversational-agent–assisted health-coaching system that supports the delivery of preventive health interventions for individuals and groups.

Constructive Social Choice (CSC)

Constructive Social Choice (CSC) investigates group decision-making in combinatorial domains where recommended items must be generated rather than selected from a predefined set. 

Adaptive Cobotics develops collaborative robots with adaptive, reactive motion control for dynamic production environments. Using reinforcement learning informed by biomechanical, neural, and physiological signals, the goal is fluid, safe, and continuously responsive human–robot collaboration.

Adaptive Cobotics