Thematic Session 28

THEMATIC SESSION #28

Pietro Cipresso

Department of Psychology, University of Turin, Italy

• pietro.cipresso@unito.it

Francesca Borghesi

Department of Psychology, University of Turin, Italy

• francesca.borghesi@unito.it

Understanding affective processes in human behavior requires an interdisciplinary approach that integrates robust quantitative methodologies with cutting-edge technological tools. This thematic session explores the complex dynamics of affect regulation by leveraging stochastic modeling, virtual reality (VR), and innovative digital tools to advance both theoretical insights and applied research in psychology and psychometrics.

Affect dynamics are inherently nonlinear, context-dependent, and probabilistic, necessitating analytical frameworks that go beyond traditional statistical models. Stochastic methods, including Markov processes, dynamical systems, and Bayesian approaches, offer a powerful means to capture the fluctuating and unpredictable nature of emotions over time. By modeling affect as a stochastic process, we can uncover underlying structures in emotion regulation, resilience mechanisms, and patterns of mood variability, with significant implications for both clinical and experimental psychology.

Complementing these approaches, virtual reality provides a highly controlled yet ecologically valid environment for studying affective responses. By immersing individuals in adaptive, interactive simulations, VR enables researchers to manipulate contextual variables in real-time, assess physiological and behavioral reactions, and refine computational models of affective states. Integrating VR with biometric and psychophysiological measures (e.g., heart rate variability, electrodermal activity, eye tracking) further enhances our ability to quantify emotional fluctuations and personalize interventions.

This session also focuses on emerging technologies and computational tools - from wearable devices to AI-driven affect recognition - that are reshaping the landscape of affective science. These tools enable real-time monitoring and intervention, fostering new perspectives in mental health, human-computer interaction, engineering and psychological assessment.

Bringing together experts from psychology, neuroscience, data science, and human-computer interaction, this session invites contributions that explore:

• Stochastic modeling of affect and emotional regulation;
• Virtual reality as an experimental and clinical tool for affective science;
• Wearable and biometric technologies for real-time affect assessment;
• AI and computational approaches in emotion prediction and intervention;
• Methodological innovations in capturing and analyzing affective dynamics.

By bridging stochastic modeling with immersive and technological solutions, this session aims to foster a more nuanced, predictive, and application-driven understanding of affect dynamics, ultimately advancing psychological research and practice.

Pietro Cipresso is a Professor of Psychometrics at the University of Turin and a Senior Researcher at the Istituto Auxologico Italiano in Milan. His research focuses on the intersection of computational psychometrics, affective science, and innovative methodologies for psychological assessment. He has extensive expertise in stochastic modeling, virtual reality, and advanced statistical methods, applying these approaches to study affect dynamics, human behavior, and mental health. As an author of numerous scientific publications, he has contributed to the development of novel quantitative frameworks for psychology, integrating AI, machine learning, and immersive technologies. His work spans both academic and applied domains, aiming to enhance psychological research through interdisciplinary innovation.

Francesca Borghesi is a researcher and expert in psychometrics, computational methods, and affective science, with a strong focus on emotion dynamics, experimental psychology, and data-driven modeling. Her work integrates stochastic approaches, physiological measures, and digital tools to investigate affect regulation, decision-making, and psychological well-being. She has collaborated on interdisciplinary projects involving virtual reality, biometric data, and machine learning to refine psychological assessments and interventions. Passionate about methodological advancements, she contributes to bridging theoretical psychology with emerging technologies, aiming to develop innovative frameworks for understanding human emotions and behavior.