Cohort: ESOL 41

Topic of the thesis:  From Sensors to Structure: An Integrated Approach to Computational Proxemics

Abstract: This research project introduces a novel, integrated approach to the study of interpersonal distance regulation in naturalistic settings. By combining wearable proximity sensors, smartphone sensors, ecological momentary assessments, and survey data, the methodology enables real-time monitoring of interpersonal spacing, while also capturing static and dynamic attributes of the individuals involved. Spatial arrangements are formalized as time-dependent graphs, allowing for the reconstruction of proximity networks and the adoption of a structural perspective in analyzing spatial behavior. Drawing on advancements in computational network modeling, the analytical framework supports the investigation of spatio-temporal patterns of proximity regulation and the emergence of structural properties within evolving social networks. Ultimately, this project advances a new approach to reality mining by leveraging the integrated use of technology-enhanced sensing devices to overcome key limitations inherent to traditional methods, particularly those related to human observation and retrospective self-reporting.

Research interests: Computational Proxemics; Network Analysis; Computational Modeling; Sensor-Based Monitoring; Smartphone Sensing; Ecological Momentary Assessment; Spatio-Temporal Dynamics

Graduated from: Sapienza Università di Roma (BA); University of Trento (MA). 

Degrees obtained: BA in Sociology; MA in Sociology and Social Research.

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