Thu, Feb 25, 2021 @ 09:00 AM - 10:30 AM
Title: Control Theoretic Framework for Measuring, Modeling, and Regulating Human Interaction
Shrikanth Narayanan (chair)
Tom D Lyon
Human interaction is a vital component to a persons' development and well-being. These interactions enable us to over come obstacles and find resolutions that an individual might not be able to. This subject is particularly well studied in the domains of human psychology, where human behavior is diagnostically categorized and the interaction can be utilized in order to improve somebody's health.
Prior work has explored the use of computational models of human behavior to aide in the diagnostic assessment of behavioral patterns. Most recently, novel machine learning methods and access data has invited the to study the dynamics of human interaction on a more granular time-resolution. These dynamics have been used to identify specific moments during interactions that are relevant to the over all assessment of a individuals behavior with respect to their interlocutor. By reformulating this system from the perspective of an operator that can be controlled, it invites the possibility to predict how an individual would react to a specific input from their partner, which itself lends the opportunity to plan out interventions and probes more effectively.
This thesis proposal presents a formulation of human interaction as a control theoretic problem and demonstrates how these frameworks can be utilized to gain insight into improving desired outcomes. In support of the thesis, we will present the application of these techniques to the domain of child forensic interviewing.
Presentation on: February 25th 9 a.m. join via Zoom: https://usc.zoom.us/j/93374500380?pwd=ZHh6UDVXV0NTei9OS3h6TlZCeitDUT09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon